ure 6. The CCL2/CCR2 A
Figure 6: Mouse model with CCL2 A) Shows the tumors on the mice B-D) Modulating metastatic potential with CCL2 and CCR2 Switch to Sonic Hedgehog because a critique was whether the blood-brain barrier was damaged with injection. This shows the metastatic development spontaneously and without injection through BBB
re 5. The CCL2/CCR2
Figure 5: CCL2 is ligand, CCR2 is receptor A-D) Adding CCL2 makes it metastatic E -F) Removing CCL2 reduces metastasis
igure 4. CCL2 Overe
Figure 4: In vivo into systemic: RNA seq from human samples A) Difference between primary and metastases is CCL2 B) Premetastatic --> Less CCL2+, post metastatic = more CCL2+ C) Higher proportion GOF in metastatic --> Smaller sample sizes are because it's hard to get those metastatic samples D)
igure 3. Hematogenous Dissemination of Medul
Figure 3: Parabiosis A) Sew mice together and let peritoneal and vasculature combine --> Exchange blood, but not CSF --> Schema B) Shows that circulatory systems are fully merged. C) Shows high colonization even without CSF D) Shows similar leptomeningeal effect E) Quantization of D
gure 2. Circulating Medullobla
Figure 2: A) Shows the different population cells came from. Came from mouse models with GFP, then xenograft models. Both engineered and patient derived show GFP, so both models work. B) Is there a difference in survival between mice with grafted from a primary or spinal mets --> schema C) Not much difference in survival D) Higher frequency of metastatic cells in Met derived tumors E) Remove the primary tumor, then look at metastases. Metastases can continue without primary tumor. Also allows for metastases to grow larger without risking mortality from primary tumor. --> Mirrors human patient treatments, we remove the primary tumor when possible.
Figure 1. Circulating Medulloblastoma
Figure 1: A) Whole genome sequencing of primary, metastatic, and blood, all matched from one individual B) Clonality --> There are difference for tumor cells that are circulating C) NCAM (Neural adhesion) -> brain origin, identify where tumors came from. NCAM- = not brain, NCAM+ = brain, CD45- means they are not WBCs D) Image-Stream Flow: Single-cell imaging of circulating tumor cells. Hoescht+ = nucleated E) Histology, stained for NCAM, very diffuse NCAM+ presence, NCAM is a good marker
raphical Abstr
Correcting misconception --> tumor not only disseminating through CSF, blood too
INTRODUCTIO
This is actually 4 different diseases: Myc Driven Myc amplified --> most deadly
Most of the children who die from this disease die from the metastases.
Can't take metastases --> like removing butter after its been spread on bread
ugh the lymphatic system and were taken up by lymphatic endothelial cells, reinforcing lymph nodemetastasis. Remarkably, sEVs enhanced lymphangiogenesis and tumor cell adhesion by inducing ERK kinase, nuclear factor(NF)-κB activation and intracellular adhesion molecule (ICAM)-1 expression in lymphatic endothelial cells. Importantly, abla-tion or inhibition of NGFR in sEVs reversed the lymphangiogenic phenotype, decreased lymph node metastasis and extendedsurvival in pre-clinical models. Furthermore, NGFR expression was augmented in human lymph node metastases relative tothat in matched primary tumors, and the frequency of NGFR+ metastatic melanoma cells in lymph nodes correlated with patientsurvival. In summary, we found that NGFR is secreted in melanoma-derived sEVs
NGFR is critical to early melanoma metastases Tumors change microenvironment to make favorable niches
Fig. 8 | EV-shed NGFR favors LN metastasis and influences survival. a,b, Representative images (a) and quantification (b) of mCherry+ B16-F1 cells inpopliteal LNs. Mice were educated with B16-F1-GFP-derived and B16-F1-NGFR–GFP-derived sEVs as in Fig. 1i. Data were collected from two independentexperiments (n = 10 mice per group; GFP group, 28 LN sections and NGFR–GFP group, 26 LN sections). Scale bars, 200 μm and 40 μm. c,d, Representativeimages (c) and quantification (d) of mCherry+ B16-F1 cells in popliteal LNs. Animals were educated with control or Ngfr-KO B16-F1R2-derived sEVs asin Fig. 1i (n = 5 mice per group; control group, n = 21 LN sections and Ngfr-KO group, n = 24 LN sections). Scale bar, 20 μm. e, Metastatic area in miceeducated with control and Ngfr-KO B16-F1R2-derived sEVs as in Fig. 1k. Two independent experiments were performed (n = 9 mice per group). f, Survivalof animals educated with control and Ngfr-KO B16-F1R2-secreted sEVs as indicated in e (control sEVs, n = 12 mice and Ngfr-KO sEVs, n = 10 mice).g–i, Percentage of animals (g), number of LN metastases (h) and representative images (i) in animals bearing B16-F1R2 flank tumors untreated ortreated with THX-B as in Fig. 7j (vehicle, n = 7 mice and THX-B, n = 8 mice). Met, metastasis. j, NGFR h scores in skin and LN sections from patients withmelanoma (n = 26 skin or soft tissue samples and n = 17 LN samples). k, Percentage of NGFR+MITF+ tumor cells in skin and LN samples from patientswith melanoma (n = 21 matched samples). l, Overall survival (OS) of patients with stage II or III melanoma according to NGFR+MITF+ cell numbers in LNbiopsies (less than 75 NGFR+MITF+ cells, n = 13 patients;
NGFR KO had prolonged survival Patients NGFR+ correlated with decreased survival
ig. 6 | Melanoma-derived sEVs activate NGFR, MAPK and NF-κB signaling pathways in LECs. a,b, Representative images (a) and quantification (b) ofp65 staining in HLECs after exposure to TNF-α or SK-MEL-147-derived sEVs for the indicated times. Arrows indicate cells with p65 nuclear staining (n = 5samples per group). Scale bar, 50 μm. c,d, Representative confocal images (c) and quantification (d) of p65 staining in HLECs in basal conditions or afterthe addition of TNF-α or shC or shNGFR SK-MEL-147-derived sEVs for 30 min. p65 translocation was analyzed using a confocal high-content screeningsystem. Plot shows data from one of two representative experiments (control, n = 5,325 cells; control shC, n = 3,355 cells; and shNGFR, n = 3,005 cells).Scale bar, 40 μm. e–g, Representative confocal images (e), quantification of nuclear area (f) and average fluorescence intensity (g) of staining forp65 in HLECs exposed to SK-MEL-147-derived sEVs in the presence or absence of the NF-κB inhibitor JSH-23 or the NGFR inhibitor THX-B. Data werecollected from two independent experiments (n = 12 samples per group, except for THX-B and JSH-23 groups (n = 7 samples for f and n = 6 samplesfor g)). h,i, Representative western blot (h) and quantification (i) of ERK1/2 phosphorylation levels in HLECs treated with shC and shNGFR SK-MEL-147-derived sEVs for the indicated times. Data were collected from four independent experiments (n = 4 samples per group). j,k, Representative confocalimages (j) and quantification (k) of phospho-ERK1/2 in HLECs in basal conditions or after the addition of shC or shNGFR SK-MEL-147-derived sEVs for30 min. Phospho-ERK1/2-associated cell fluorescence was analyzed using a confocal high-content screening sy
NGFR inhibitor shows that NGFR is what give the result. MAPK does similar things.
NGFR is important for all of this, dependent on NGFR expression
cytes and melanoma cell lines (top) or murine cell lines (bottom). Two independent experiments were performed (n = 2 samplesper group). b, Representative overlay flow cytometry plots of staining for NGFR in SK-MEL-28-derived and SK-MEL-147-derived sEVs. Two independentexperiments were performed (n = 2 samples per group). c, NGFR mRNA levels in hLECs treated for 24 h and 48 h with SK-MEL-147-derived sEVs or CM.Data were obtained from two independent experiments (n = 4 independent cell cultures per group, except for 24 h, sEVs, n = 6; and 48 h, sEVs and CM,n = 5). d, Representative images of staining for NGFR in HLECs exposed to SK-MEL-147 sEVs for 48 h. Three independent experiments were performed(n = 6 cell culture samples per group). Scale bar, 30 μm. e, NGFR mRNA levels in hLECs exposed to sEVs from melanocytes or different melanoma cell linesfor 48 h. Data were collected from two independent experiments (n = 6 sa
sEVs treatment increases proliferation --> increase metastasis. nGFR more prevalent in more metastatic cell lines Works in human metastic cell lines
eq data (all groups, n = 3 samples per group). b, Expression of lymphangiogenesis-related and/or angiogenesis-related genes in hLECs treatedwith SK-MEL-147-derived sEVs or control hLECs. Data were obtained from two independent experiments (n = 6 independent cell cultures per group).c, Representative western blot of p-VEGFR3 and total VEGFR3 levels in HLECs treated with SK-MEL-147-derived sEVs. Three independent experimentswere performed (n = 3 samples per group). GAPDH, glyceraldehyde-3-phosphate dehydrogenase. d, Representative images of endothelial cell tube assaysperformed in HLECs growing on matrigel for 16 h after treatment with SK-MEL-147-derived sEVs. Data were obtained from three independent experiments(n = 15 samples per group). Scale bar, 100 μm. e,f, Representative images (e) and quantification (f) of LYVE-1+ cells in control (PBS) and SK-MEL-147-derived sEV-embedded matrigel plugs. Data were collected from two independent experiments (control, n = 5 plugs and sEVs, n = 4 plugs). Scalebar, 50 μm. g, Representative images of consecutive sections of an sEV-embedded matrigel plug stained for LYVE-1 and F4/80 (n = 4 plugs per group).Scale bars, 250 μm and 80 μm (inset). h,i, Representative images (h) and quantification (i) of luminescence in LNs of Vegfr3-EGFP-Luc mice after 7 d ofexposure to B16-F10-derived sEVs. Data were obtained from three independent experiments (popliteal control, axillary control and inguinal sEV groups,n = 3 LNs; inguinal control groups, n = 2 LNs; axillary sEV group, n = 4 LNs; popliteal sEV group, n = 5 LNs). j,k, Representative images (j) and quantification(k) of LYVE-1 staining in LNs after 48 h of intra-footpad injection with B1
Does Melanoma derived sEVs promote Lymoh Angiogeneis in LECs?
Hypothesis: VEGFR3 activation will occur promoting prolymphangiogeneic growth
Results: It does, even in F1R mice
racellular matrix; JAK, Janus kinase; PPAR, peroxisome proliferator-activated receptor; STAT, signal transducer and activator oftranscription. b, Correlation between RNA-seq data in hLECs and proteomic data in SK-MEL-147-derived sEVs. The color code indicates significantlyregulated gene–protein pairs (FDR < 0.05). FC, fold change; ITGB, integrin subunit β; VCAN, versican. c, Top pathways significantly enriched in the groupof positively correlated gene–proteins pairs shown in b. Pathways were obtained using PANTHER over-representation analysis by applying Fisher’s exacttest and FDR correction. d,e, Representative images (d) of PKH26-labeled SK-MEL-147 cells adhered to sEV-treated LECs in flow. LECs were previouslyexposed to PKH67-labeled sEVs from primary melanocytes (melano) or SK-MEL-147 cells for 24 h. The plot in e shows quantification of attachedtumor cells at t = 4 h. Two independent experiments were performed (all groups, n = 20 fields from one representative experiment). Scale bar, 50 μm.f, ICAM1 expression in hLECs treated with SK-MEL-147-derived sEVs for 48 h. Two independent experiments were performed (n = 6 LNs per group).g,h, Representative images (g) and quantification (h) of ICAM-1 expression in LNs treated with B16-F1R2-derived sEVs intra-footpad for 10 d. Two independentexperiments were performed (n = 7 LNs per group). Scale bars, 100 μm and 200 μm. i, LYVE-1 and ICAM-1 staining in LNs treated with B16-F1R2-derivedsEVs or PBS for 48 h (n = 3 LNs per group). Scale bar, 50 μm. j, Quantification by flow cytometry of LECs expressing high levels of ICAM-1 in LNs ofanimals injected intra-footpad with B16-F1R2-derived sEVs for the indicated times. Two independent experiments were performed (control and 48 h,n = 3 LNs per group and 7 d, n = 4 LNs per group). k,l, Representative images (k) and quantification (l)
Hypothesis: Human cells will show similar effects as the mouse model and will have up & down regulated genes
Conclusion: Found genes positively correlated --> nGFR in particular. Melanoma derived sEVs influence LEC phenotype and promote cell adhesion. Block ICAM prevents adhesion
oup). Scale bars, 100 μm and 20 μm. b, Representative images of cervical LNs 16 h after intra-footpad injection of PKH26-labeled B16-F1-derivedand B16-F10-derived sEVs. Arrows indicate areas of overlapping PKH26 and LYVE-1 staining (n = 3 mice per group). Scale bars, 200 μm and 20 μm.c, Representative images of two consecutive popliteal LN sections dissected 16 h after intra-footpad injection of DiD-labeled B16-F1R2-derived sEVs.White lines delineate areas of stained lymphatic (top) and macrophage (bottom) networks (n = 3 LNs per group). Scale bars, 250 μm and 50 μm.d,e, Representative flow cytometry plots (d) and quantification (e) related to B16-F10-derived sEV uptake in the indicated stromal and immunepopulations. DiD-labeled sEVs were injected intra-footpad, and LNs populations were analyzed 16 h later. Gates were depicted based on the correspondingdye-only signal for each population. The gating strategy is shown in Extended Data Fig. 2b. Three independent experiments were performed (n = 4LNs analyzed). C, dye-only control LNs; sEVs, DiD-sEVs exposed LNs; BECs, blood endothelial cells; FRCs, fibroblastic reticular cells; cDCs, classicaldendritic cells; pDCs, plasmacytoid dendritic cells. f, Representative plots of B16-F1R2-derived sEV-associated fluorescence in LECs and CD169+F4/80+macrophages 4 h after intra-footpad injection. Three independent experiments were performed
Hypothesis 1: Are sEVs taken up differently in different cell lines
Conclusion: Tumor sEVs are taken up by LECs and Macrophages
ntralateral LN; RFU, relative fluorescent units. d,e, Representative images (d) and quantification (e) of sEV-associated signal in mice 1, 4, 24and 48 h after intra-footpad injection with NIR815-labeled sEVs. Data correspond to two independent experiments (n = 4 mice per group). Squaresindicate popliteal LN area. f, Representative images of the distribution of melanoma DiD-labeled sEVs (DiD-sEVs) in popliteal LNs 16 h after intra-footpadinjection (n = 4 LNs per group). Scale bar, 150 μm. DAPI, 4′,6-diamidino-2-phenylindole. g,h, Representative flow cytometry plots (g) and quantification(h) of GFP+ B16-F1 cells in the CD45− population in LNs educated with sEVs for 10 d. LNs were analyzed 24 h after injection of tumor cells (PBS andB16-F1R2, n = 5 mice per group; B16-F1 and B16-F10, n = 4 mice per group). i,j, Representative images (i) and quantification (j) of mCherry+ B16-F1 cellsin sections of popliteal LNs 10 d after tumor cell injection. Melanoma-derived sEVs or PBS were injected intra-footpad for 10 d before tumor inoculation.Two independent experiments were performed (control, B16-F1 and B16-F1R2 groups, n = 5 mice per group; F10 group, n = 4 mice). Scale bar, 20 μm.k,l, Representative images (k) and quantification (l) of metastatic area in inguinal LNs of animals bearing B16-F1-GFP flank tumors and educated withB16-F1R2 sEVs injected intra-footpad for 21 d. LNs were stained against human melanoma black 45 (HMB-45) antigen. Two independent experiments wereperformed (n = 12 mice per group). Scale bars, 500 μm and 200 μm. B
Hypothesis: Do the different mouse melanoma cell lines show different spread through the lymph nodes
Results: F10 are more enriched that F1 cells
Hypothesis 2: Does lymphnode education change the spread of cancer cells through lymph nodes accross cell lines.
Results 2: Increased GFP activity in lymph nodes in F10, but GFP is eliminated in immunocompetent mice, soo...
Hypothesis 3: Does popliteal lymph node education effect these?
Results 3: F10 were able to establish and colonize popliteal lymph node
Melanoma derived extracellular cicrulate in lymph nodes and enhance melanoma metastases
hematic figure showing experimental strategy.(B and C) Whole-mount fluorescence images of lungs collected from N-cad-EMTracer;MMTV-PyMT (B) and N-cad-EMTracer (C) mice.(D and F) Immunostaining for ZsGreen, tdTomato and PyMT on lung sections shows ZsGreen+ colony (green asterisk), tdTomato + colony (red asterisk),ZsGreen + tdTomato + colony (yellow asterisk), and ZsGreen –tdTomato – colony (white asterisk). Large size lung metastasis (D) and small size lung metastasis (F).(E) Quantification of the percentage of ZsGreen +tdTomato–, ZsGreen –tdTomato +, or ZsGreen + tdTomato + colony number among all fluorescent colonies.(G) Immunostaining for tdTomato and N-Cad on lung sections.(H) Schematic figure showing experimental strategy for knockout N
Figure 6: N-Cadherin activity is present during tumor growth and metastasis A) Scheme B and C) Looking at lesions --> Late stage tumor nodules, N-Cadherin is present, important for metastasis D-G) Shows higher % of N cadherin expression in the lung tumors ~65% H-O) New model, western blot confirm, N-Caherin is required for metastasis, about 60%
Earlier assumed that EMT turned on all of mesenchymal machinery, portions of mesenchymal will be activated, not entire. Cancer is not one size fits all, so not every mesenchymal marker will be displayed.
CS isolation of ZsGreen + and tdTomato + cells from N-cad-EMTracer;MMTV-PyMT mammary tumors.(B) qRT-PCR of RNA expression of epithelial cell marker E-Cad; EMT markers N-cad and Vim; EMT transcriptional factors Zeb1, Twist, and Snail in ZsGreen+ cellsor tdTomato + cells. Gene expression in ZsGreen + cells is set as 1. Data are mean ± SEM; n = 5; *p < 0.05.(C) Cell invasion assay using transwell shows more invasion in tdTomato + cells than ZsGreen + cells. Number of relative cell invasion in ZsGreen + cells is set as 1.Data are mean ± SEM; n = 5; *p < 0.05.(D) Immunostaining for Zeb1 and IgG control (left panel) shows specific Zeb1 staining on mammary tumor sections. Immunostaining for tdTomato and Zeb1 onmammary tumor sections (right panel) shows a subset of tdTomato + tumor cells expressing Zeb1 (yellow arrowheads).(E) Schematic figure showing experimental strategy for searching circulating tdTomato+ tumor cells by high-throughput screening.(F) Image showing a microwell chip platform that accommodates 400 numbered blocks with over 100,000 addressable microwells.(G) Fluorescence images of ZsGreen + or tdTomato + cells in microwells of the chip. Arrowhead indicates tdTomato + EpCAM +circulating tumor cell that hasundergone N-cad + EMT.(legend continued on next page)llArticle
Figure 7: Additional EMT markers are upregulated in mammary tissue A-D) Did by qPCR, Zeb is for pancreatic cancers. E) New model with blood samples F-I) Looked at samples during N-cadherin while active to see if N-Cadherin is activated during extravasation. N-Cadherin is less activated during extravasation and lung colonization. H) Control without fluorescent marker
(A) Whole-mount fluorescence images of mammary and lung of N-cad-EMTracer mouse. Inserts are bright-field images. Tamoxifen was induced at 7 weeks andtissues were collected at 18 weeks.(B) Immunostaining for ZsGreen, tdTomato, and E-Cad on mammary and lung sections of N-cad-EMTracer mouse. No tdTomato + cells were detected inmammary and lung epithelial cells.(C and H) Whole-mount fluorescence images of mammary tissue collected at early (8–12 weeks) (C) or late (18–24 weeks) (H) stages from N-cad-EM-Tracer;MMTV-PyMT mouse. Inserts are bright-field images.(legend continued on next page)llArticle
Figure 5: N Cadherin --> Control Figure A) Control to show that model works and is not unspecific B) Control to show that model works and is not unspecific C -G) Early stage tumor, lots of green, N cadherin is not expressed in early stage H-L) Late stage tumor, some red, N Cadherin is more involved in later stage tumors
) Immunostaining for Vim, ZsGreen, and tdTomato on mammary tumor sections.(B) Schematic figure showing experimental strategy for analysis of mammary tissues and lungs from Vim knockout mice.(C) Whole-mount fluorescence and bright-field images of mammary tumors.(D) Immunostaining for ZsGreen, tdTomato, and PyMT on mammary tumor sections. Yellow arrowheads, PyMT + tdTomato + cells.(E) Whole-mount fluorescence images of lungs with tumor metastases. Most tumor metastases are ZsGreen + but not tdTomato +.(F) Immunostaining for ZsGreen, tdTomato, and PyMT on lung sections. Yellow arrowheads indicate very few PyMT +tdTomato + tumor cells in the large tumormetastases in the lung.Scale bars, yellow, 2 mm; white, 100
Figure 4: Vimentin is activated during growth and expansion of metastasis A) Knock out B) Schema C) D) E) F) Lung metastasis subset shows promotor is active, involved in growth, but not present at site. Upregulated but not important for metastasis
Schematic figure showing experimental strategy. Mammary and lung tissues were collected for analysis at early stage (B–D) and late stage (E–M).(B) Whole-mount fluorescence image of mammary tissue and lung. T, tumor nodule.(C) Immunostaining for PyMT, ZsGreen and tdTomato on sections from mammary tissue. Arrowheads indicate tdTomato +PyMT + tumor cells.(D) Quantification of percentage of ZsGreen + or tdTomato + cells in PyMT + tumor cells. Data are mean ± SEM; n = 5.(E) Whole-mount fluorescence image of primary tumor at late stage.(F) Immunostaining for PyMT, ZsGreen and tdTomato on mammary tumor sections. Arrowheads, PyMT +tdTomato + tumor cells(G) Quantification of percentage of ZsGreen + or tdTomato + cells in PyMT + tumor cells. Data are mean ± SEM; n = 5.(H) Immunostaining for vimentin, ZsGreen, and tdTomato on mammary tumor sections. Arrowheads, Vimentin + tdTomato + tumor cells.(I) Whole-mount fluorescence image of lung at late stage. Small size lung metastasis (1, <0.1 mm, arrow) and large size lung metastasis (2, >0.5 mm).(J and L) Immunostaining for PyMT, ZsGreen, and tdTomato on lung sections. In small size nodules, PyMT+ tumor cells are ZsGreen +tdTomato – (J). In large sizenodule, most PyMT + tumor cells are ZsGreen +tdTomato –, while a minority of PyMT + cells are ZsGreen –tdTomato + (arrowhea
A) Stratgey B) A lot of green --> Lots of primary tumors in the mammary gland --> very potent. No vimentin in the lung C) Each stain individually then merged, making sure that only looking at tumor cells. --> Green is cancer. Very little vimentin in breast. d) quantification of C e-h) Vimentin is not that important in breast cancer. Increases, but not much after expression. I) Small nodules in lungs J and K) Only green tumors, no red tumors L and M) Large nodules N) PCR control that stop codon was cleaved --> Proves stop was removed. Small vs large --> early versus late stage Stained for vimentin because the Cre model could stop fluorescing, the stain shows if vimentin was ever expressed
A) Schematic showing strategy for Cre-loxP mediated conventional lineage tracing of transient EMT status. Labeling efficiency depends on inducible CreERactivity; temporal activation of CreER by pulse induction of tamoxifen may not capture transient mesenchymal gene activity.(B) Schematic showing strategy for Cre-loxP mediated Dre generation and subsequent Dre-rox recombination that switches ZsGreen to tdTomato on NR1reporter (left). After pulse Tam induction, constitutive Dre recombinase genotype is generated and driven by EMT gene promoter to monitor transient EMT geneactivity (right top). After Tam, the system would switch ZsGreen to tdTomato labeling on Kit + cells that have expressed EMT marker gene (Dre recombinase) (rightbottom).(legend continued on next page)ll Article
Figure 2 --> Can't use the conventional method A) Shows the conventional models and why they won't work. --> Temporal, can miss the EMT event B) New strategy schema to avoid temporal issues. Constitutively green, EMT is red. Transient induction of Cre to ensure that Cre doesn't have off-target issues C) Vimentin knock in --> No vimentin at homeostasis in mammary gland d) in lungs e) control without tamoxifen in mammary f) control without tamoxifen in lung g and h) Control without cre induction I and J)Control Vimentin is not active in normal mammary cells
Schematic figure showing
A) Kit-Cre model --> Did this way because the fate marking will be transient instead of permanant, like it was in previous models. Tamoxifen pulse may miss the reporter activity, Cre is on, gene is not expressed until EMT occurs B) Flow cytometry --> see tomato (kit+) cells in luminal only, basal cells are tomato - c) shows luminal cells as a picture d) looking at luminal K8 e) Shows basal layers f) Luminal cells are ER- g) luminal are kit+ --> red, basal are kit- --> green h) Same model as original paper --> little EMT thought to occur back then, Uses PyMT, strong way to start tumors. Early stages mimic BC well i) Hyperplastic v high-grade --> Kit+ luminal cells make most the population j) quantification of I k) Kit+ cells are in lungs, has metastasized
C CSCs (ALDH+CD44high) makeup 0.
First 10 CSC head and neck cancers. All look similar, but each have unique proportions of ALDH+/CD44
l surface antigens (e.g. CD44, CD133, CD34)• Enzymatic activity (e.g. Aldefluor, ALDH activity)• Hoechst dye efflux (Side population)• Label retention [PKH26 (membrane), Histone 2
Not extensive list, but good wats to look at stemness of cells --> Probably good to use for exam
evention works for high ER
Blue is environmental and genetic causes Green is just bad luck, essentially
EER): 6.9% lung, 1.08% thyroid, 0.6% brain/nervous, 0.003% pelvic bone, 0.00072% laryngeal cartilage• Correlation of lifetime risk and number of stem ce
Tissue stem cells are the ones that give rise to cancer
stic: all cells are equipotent that proliferate and/or differentiate due to intrinsic/extrinsic factorsoCSC hierarchical model: only CSCs can self-
Not one or the other, depends on cell line. How far down the differentiation path they've gone
stemness factors
Able to bring fibroblasts all the way to embryonic stem cells Circular thinking --> Inducible stem cells, which one came first, unknown
pearls in squa
Lose polarity, less stem like, but not differentiated well
ity Phenotypic het
mTor mutation is prevalent in metastasis but not primary.
nched evoluti
Yellow is primary tumor Green is the metastasis Different selective pressures, although SETD2 and KDM5C mutations occur twice by themselves --> eventually the select pressure will drive these mutations in metastatic cancer
Branched evolution of re
Grey is the mutation, not the blue. Exome Sequencing Pre-P--> Pre primary tumor Pre-M --> Pre-metastasis
etic heterogenei
Look at protein expression, huge diversity within populations
SCC
Squamous cell carcinoma --> head and neck
Enriched transcription factor DNA binding motifs are found at T-47
Motif Analysis is to find transcription factors, kind of like confidence intervals. Bigger letters is more confident that it is there. OCT1 is potential partner with ER to sustain ER activity and chromatin accessibility. Is OCT1 a target of ER? Don't know, not answered here, but could be explored later.
umulative distribution graphs show distance from Y537S mutant–specific genes to Y537S mutant–e
Open chromatin sites are enriched much sooner. More like an open promotor state. Something else is holding the chromatin open, not the ER.
Percentage of mutant-enriched or -depleted accessible chromatin regions that also exhibit ER bin
Used ATAC-SEQ to show the change in accessibility of chromatin. Maybe ER is more able to bind open chromatin sites. This isn't what's happening, so we want to see if change in chromatin that is changing this outcome.
Answer: Yes, something else is driving the open chromatin state besides the ER.
Distance from mutant-specific genes tomutant-enriched and -depleted ERBS is shown as a cumulative dist
Red line = left shift = more binding
xample locus of ligand-independent (constant) ER binding. Arrow, TSS of GREB1.
Restore to what you see in the mutants.
eatmap shows the binding signal of constant and mutant-specific ERBS in T-4
Does mutation specific gene expression change binding compared to WT. Each row is a binding location, organized --> Red = lower, Blue = Higher Tornado plot, centers on one locus.
Mutants shows genomic regions that are bound that are not found in the WT. The sites are normal binding sites, the change is in binding intensity.
It is not new binding sites that are driving biology
To investigatethis possibility, we performed ChIP-seq experiments on WT andmutant T-47D and MCF7 clones, grown for 5 days in hormone-depleted media followed by 1-hour E2 or DMSO treatments, using anantibody that recognizes the FLAG epitope tag.
1 hour after E2 treatment --> To see where it's binding, no second effects from downstream.
Long-term constitutive ER activity may leadto the differential expression of genes that are in fact regulated by WTER, but do not change expression with short-term E2 treatment. Todetermine how much of mutant ER’s gene regulatory changes can beattributed to mutant ER’s constitutive activity, we treated T-47D andMCF7 WT clones with E2 for 25 days.
Go for longer term treatments. Up to 25 days have the same regulated response of ER genes. So yes, longer time still shows the same results.
(Fig. 2A, ex
Used results from different studies to ensure reproducibility and that the results are consistent across different studies. Each lab uses their own source of MCF7 cell lines, so it is more powerful that the results are still consistent.
Of these mutant-specific genes, nearly30% of D538G-regulated genes (upregulated genes, P ¼5.1e55 anddownregulated genes, P ¼1.8e59) and 15% of Y537S differentiallyregulated genes (upregulated genes, P ¼2.3e28 and downregulatedgenes, P ¼7.04e17) were shared across both cell lines (T-47D andMCF7, examples in Supplementary Fig. S2D)
Cell lines have different interactions, even between patients with the same cancer. Most cell lines are from metastatic cancers from plural fusion from different sites. They are easier to get. Many cell lines are not primary cell line because they are difficult to obtain.
Heatmap shows expression levels for ligand-independent, mutant-specific shared, and allele-specific genes.
Ligand Independent --> Independent of ER binding. Should show up in WT. Find Estrogen repressed and Estrogen expressed genes. Mutations make E2 effects more robust in the presence of E2. Mutants have initial expression levels that are ligand independent.
Mutant-Specific Shared --> Mutants have higher Z-Score than downregulated genes in DMSO and in E2 presence, while mutants have lower Z-Score than upregulated genes in DMSO and in E2.
Y537S allele specific --> Y527S shows opposite response of WT and D528G, which are the same
D528G allele specific --> D528G shows opposite response of WT and Y527S, which are the same
we performed RNA-seq onWT and mutant clones grown in hormone-depleted media and treatedwith E2 or DMSO for 8 hours.
Removed estrogen from the media --> Comes from FBS, plenty to keep ER active even in low concentrations. Use activated charcoal to remove estrogen. This also takes out steroids and other hormones. Targets lipolitic things.
8 hour time frame --> Isolates only what ER are doing. This more or less the minimum time to do this.
To characterizeendogenous ER mutations, we created multiple isogenic clonal linesthat heterozygously express FLAG-tagged mutant or WT (control) ERfrom the endogenous locus (Supplementary Fig. S1A; ref. 22). Wedeveloped two clones each for WT and the two most common ER LBDmutations (Y537S and D538G) in both T-47D and MCF7 breast cancercell lines (Supplementary Fig. S1B). Engineered lines included a FLAGepitope tag at the C-terminus to allow for downstream analyses. Theheterozygous expression of FLAG-tagged mutant or WT ER and theavailability of multiple clones per genotype provided a robust system toinvestigate mutant ER’s molecular effects.
ER is an ER regulated gene, gives the extent of estrogen receptor effects. Uses multiple clones because all of the cells are genetically identical. Want to rule out that clones are doing something that is a clone effect independent of your study. This also helps to reduce likelihood that the CRISPR mutation didn't have off target effects that influenced the results.
Y537S and D538G.
Most common mutations in the ligand binding domain
gure 7. Proposed model for the role of autophagy in colorectal carcinogenesis associated with CoPEC colonization. In ahost predisp
Figure 7: Model for role of autophagy Therapy: If you are a patient with CoPEK+, do not want autophagy inhibitors.
4 Lucas e
Figure 6: Cell cycle, CRC, knockdowns at day 65, upregulation of Cyclin 1 (Cell Cycle Progression) a) Knockouts = more Cyclin D1 = cell cylce progression b) Quantification of band intensity c) Quantification of Cyclin D1 mRNA d-e) Shows more cell growth in knockout cells f-g) Shows more cell proliferation in knockout cells
igure 5. Autophagy
Figure 5: Putting it together. Mouse model deficient in autophagy. Treat with 11G5 or PBS. a-b) Western blot--> Control --> No induction of LC3II c-d) Western for DS DNA breaks, more in knockout. e-f) Presence of CoPEK -> More DNA damage.
igure 4. A
Figure 4: Same mouse model --> PBS or 11G5, look at inflammatory markers Increase in IL6, Cxcl1, and TNF Decreased IL10: Immune suppression
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Figure 3: Start using mouse model. Used APC autophagy knockdown. Use PBS (control0 a) Presence of CoPEK = lower weight 11g5 severely reduces healthy weight of mice. Lose autophagy, worse weight loss. Need bacteria present to have the weight loss. Weight loss is bacteria dependent and need CoPEK for the weight loss b) Visualization of mouse colons: Colon is shortened and has tumors in autophagy negative, bacteria mice c) No autophagy and no bacteria = better outcomes. d) Bacteria is enough to set over edge if no autophagy e) More adenocarcinomas/tumors in knockdown mice without autophagy in presence of CoPEK
Autophagy is shown to show protective role in tumor formation
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Figure: CoPEK Bectin 1 effect on the cell through DNA DS Breaks a) Showed DS DNA breaks with gamma H2AX, knockdown has more DS breaks that scramble --> no autophagy = more DS DNA breaks c-d)Quantification of WB band intensity, Fluorescence and quantification e) Knock out atg5 --> Consistent Rad51, knock out p62 = rescue of Rad51. Shows DNA repair f) Ratios of RAD51 to housekeeping gene g) IF shows that knockdown of 11g5 rescues Rad51 h) Quantification of g
METHODS
SQSTM1 -> nO autophagy = no DNA repair Used APC Mice for LOF in APC genes Used Flox model for rescue of function
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Figure 1: Isolated CRC tissue and treated with CoPEC or PKS - bacteria. a) Treat with CoPEC = Increase of autophagy b) CoPek treated have less under median than PKS- bacteria c) Western blot --> CoPEK strains upregulated LCG2 --> Autophagy d) Visualization of c 3) Time course PKS island is important for phagosome construction f) LC3 increase in 11G5 , SQSTM1 shows decreased in 11G5 g) KNockdown of autophagy --> Does autophagy increase CoPEK. More bacteria in cell after infection with ATG5 knockdown h) Lack of autophagy shows increase in inflammation with ATG5 knockdown.
BACKGROUND & AIMS
Autophagy linked to CRC CRC Microbiome dominated by Colibactin-Producing E coli (CoPEC) What role does autophagy play in CoPEC driver CRC
ion (mean ± SEM) of c
Knock down MAPK4 increases susceptibility to inhibitors, rescue still shows susceptibility. a) MDA-MB-231 don't normally respond to PI3K inhibitors, do with KO and rescue b) Knock out cell line has decreased growth to wt, add PI3K inhibitor decreases cell growth further. c) Knock-out plus inhibitor have smallest tumor size.
and c wild type (WT) and MAPK4-knockout (KO, clone #2) SUM159 cells, as well as MAPK4-KO SUM159 cells with ectopic expression ofMAPK4 (KO-MAPK4). The cells were also treated with PI3K inhibitors LY294002, Pictilisib, Alpelisib at the indicated concentrations, or vehicle control(DMSO). Representative images a
Anchorage independent growth a-b) knockdown MAPK4 plus PI3K or MAPK inhibitor = no change, add makes it different. Shows MAPK4 could be an alternative pathway, removing makes it more susceptible to treatment c) knockout is similar to knockdown, reintroduce to knockout doesn't fully rescue. d)
rmation assay data of engineered a SUM159, b MDA-MB-468, c HCC1395, and d HCC1806 cells with 0.5 μg/ml Dox-induced ectopic expressionof MAPK4 (iMAPK4) or control (iCtrl). The cells were also treated with increasing doses of Pictilisib, Alpelisib, or control. The right panels showquantification of colonies formed und
This time knocks-in and add inhibitor brings down to basal levels. a-d) dose response e) PI3K inhibitors also have additive effects
ntrol (iNT). The cells were also treated with increasing doses of Pictilisib, Alpelisib, or control. e Representative images and quantification of SUM159-iNT and -ishMAPK4 cells in the colony formation assays. The cells were treated for 10 days with PI3K inhibitors Pictilisib (1 μM), Alpelisib (0.5 μM),LY294002 (2 μM), or DMSO. The right pan
Knockdown of MAPK4 sensitizes TNBC cells to PI3K inhibitors a-d) Dose response of PI3K inhibitors in response to MAPK4 knockdowns 3) MAPK4 knockdown is additive with PI3K and AKT inhibitors f) Knockdown MAPK4 plus Alpelisib is the best
ig. 4 MAPK4 promotes TNBC xenograft growth in vivo. Dox-induced knockdown of MAPK4 inhibits a MDA-MB-231 and b HCC1937 xenograft growthin SCID mice. c Dox-induced overexpression of MAPK4 promotes SUM159 xenograft growth in SCID mice. 2 × 106 of engineered MDA-MB-231 orHCC1937 cells with Dox-ind
Dox-Induced vector knockdown once established, a) MAPK4 promotes tumorgenic growth. b) Xenograft c) Upregulate MAPK4 shows that tumors grow better in vivo d) Upregulated MAPK4 in normal cell line, increased colony formation and phosphorylation. Makes normal cell behave more like a tumor cell, did not make tumors grow in mice. 3)
g/ml Dox-induced expression of MAPK4 (iMAPK4) or control (iCtrl). The cells were also treated with 1 μM of the AKT inhibitors MK2206(left) or GSK2141795 (right) or control. Data are mean ± SD. d Representative images and quantification of soft-agar assays on Dox-induced SUM159-iMAPK4 cells treated with AKT in
AKT inhibition: d) Increasedd growth when upregulate MAPK4
knockdown of MAPK4 (ishMAPK4) or control (iNT) were induced with 4 μg/ml Dox for 3 days. The cells were then plated in 6-well plates.Twenty hours later, the cells were serum-starved overnight followed by treatments with 100 nM insulin for the indicated time (minutes). The cell lysateswere then prepared and
Insulin and EGF-Induced AKT phosphorylation independent of PI3K (Both activate RTKs) Used alpha isoform inhibitor, leaves ability of beta isoform to continue action. Doesn't quite show PI3K independence a) Add insulin in normal gains AKT phosphorylation, knock down MAPK4 then add insulin, reduced AKT phosphorylation. b) Stimulated with PI3K inhibitor, results in some reduction in AKT phosphorylation, MAPK4 downregulated PI3K inhibitor works better. c) Added EGF activates AKT phosphorylation, knock out MAPK4 gets more inhibition.
ig. 3 MAPK4 promotes TNBC cell growth in vitro. Proliferation assays comparing the growth of a engineered HCC1937, HS578T, and SUM159 cells with4 μg/ml Dox-induced knockdown of MAPK4 (ishMAPK4) or control (iNT), and b SUM159, HCC1395, and HCC1806 cells with 0.5 μg/ml Dox-inducedexpression of MAPK4 (iMAPK4) or control (iCtrl). Soft-agar assays comparing the anchorage-independent growth of the engineered c HCC1937, dHS578T, e SUM159,
Functional Assays: AKT signaling is important to tumor-like activities. a) Downregulated decreases cell proliferation b) Upregulated improves cell proliferation c-g) Knock outs and knock ins changing cancer activity g) Upregulation increases anchorage independent growth h) MAPK4 induces proliferation I) mamosphere, decrease MAPK4 decreases ability to make mamospheres
g. 2 MAPK4 activates AKT in human TNBC cells. a Western blots on MAPK4 expression in various human TNBC cell lines and MCF10A, a “normal”human mammary epithelial cell line. H157 and H1299 are human non-small cell lung cancer cell lines expressing high levels of MAPK4 as we previouslyreported. b Western blot
Used multiple cell lines to show it wasn't a fluke. a) MAPK4 expression in different cell lines, MCF10A is a normal cell line. b) Knockdown of MAPK4 reduces AKT activity c) Upregulated MAPK4 increases AKT phosphorylation and increased GSK phosphorylation, p-AKT is thought to prime d) CRISPR knockout of MAPK4 decreased p-AKT in both sites. Decreased p-GSK3B e) Rescue of function returns increased p-AKT and p-GSK3B
ig. 1 MAPK4 is highly expressed in a subset of basal-like BCa and TNBC. a MAPK4 mRNA expression across 817 BCa from The Cancer Genome Atlas(TCGA). Boxplot represents 5% (lower whisker), 25% (lower box), 50% (median), 75% (upper box), and 95% (upper whisker). Pvalue by two-sided tteston log2-transformed expression values. nrepresents independent patients. b, c MAPK4 mRNA expression across 92 BCa PDX models, including 69 TNBCPDX models. MAPK4 is
a) TNBC has highest MAPK4 expression of cancers b) Defines what high expression of MAPK4 --> above 50th percentile = TNBC c)
Targeting MAPK4 in this subset/subtype of TNBC bothrepresses growth and sensitizes tumors to PI3K blocka
Hypothesis: MAPK4 will be an important pathway in TNBC, is it expressed?
growth and reduces tumor sensitivity to PI3Kblockade
Has a previous paper that says that MAPK4 directly binds AKT
) Immunoblot
Figure 4: PLX is weak inhibitor --> Are mutants more sensitive than wt? A) VE is sensitive, but KE and KG are not sensitive, known to bind only v600E B) Same, but melanoma cell line. Insensitive as well C) Inhibitor is specific for specific mutation D) Cells lose resistance if sirt1 is knocked down. E) Double mutants are more resistant F) Only VE is sensitive to treatment G) Double mutants do not have significant difference when treated with VE specific inhibitor H) Qualitative look at tumor The acetylation site is important
Immunoblot (IB)
Figure 3: How does p300 acetylation effect MER/ERK signaling A) Different mutations, arginine mutation was similar to WT, but other mutants had lots of MEK/ERK phospho B) C) Kinase activity --> increased MEK/ERK phosphorylation D-E) Meh F) KQ results in higher tumor volume G) Qualitative tumor size comparison --> KQ is bigger H) Graphically I) Rat with tumors J) KSR with mutant are higher than wt K) Mutations effect on heterodimers L) CRAF heterodimers M) N) Myc-p300 increased scaffold protein binding O) Arginine mutant isn't as active Mutants result in increased protein interactions
) Immunoblot (IB) ana
Figure 2: Focusing on K601 of BRAF, what is the deacetylase? --> p300 A) Shows B) C) Meh D) shRNA knockdown enhances MEK and ERK signaling E) Meh F) Knockout has more MEK ERK signaling G) Sirt1 has more MEK ERK signaling H) Insulin activates p300, activates acetylation I) Small difference in pERK --> pathway turned off sooner, then later, 5 min and 40 min. J) Meh K) Knockdown effect on colony formation --> Sirt1 depends on BRAF L) Sirt1 depends on BRAF M) Xenograph into mice and graphed. Sirt1 depends on BRAF
A) Immunoblot (IB) anal
Figure 1: Jump from cell line to cell line, HEK293 is unidentified cell line. A) Can express acetylated BRAF using NMA/TSA A375 only express mutant BRAF B) Common tags, only shows p300 acetylation at lysine C) Can this be prevented with p300 inhibitor --> Yes D) Specific to BRAF? Not in A/CRaf E) Acetylation occurs at V600E F) Meh G) More p300 evidence H) Antibody for p300 works I) p300 interacts with BRAF specifically J) Mass spec shows K601R is reduced K) K601 is more biologically relevant.
p300 acetylates BRAF at K601 to promote BRAF kinaseactivit
Focused on p300, SIRT1, BRAF, MEK, and ERK
BRAF-K601 acetylation modulates the interaction of BRAFwith its binding partner
Doesn't show how reader proteins will interact
Modulation of signalling by Sprouty: a developing storyHong Joo Kim & Dafna Bar-SagiNature Reviews Molecular Cell Biology
GTP to GDP is backwards, GTP activates, so it goes GDP to GTP
They were found to exhibit electrotactic movement in response to externally applied dcEFs ofphysiological strength
Need to find physiological strength of signal required for chemotaxis without NETosis
direct current electric fields (dcEFs)
Definition
limits our understanding of the specificstimuli that initiate and modulate reverse migration.
Would be an issue if we were studying the cause of the chemotaxis, not NETosis onset; however, the two phenomena may be connected --> possible future research direction
reverse migration away from the sites of inflammation
Could be more useful than chemotaxis towards insult --> removal from stimuli may reduce likelihood of NETosis activation
first tested forchemotaxis using microfluidic devices
Strong history of microfluidics allowing chemotaxis
elatively high reagent consumption
Possibility, but sounds like it takes a long time and is not cost effective
micropipette-based assay haslow throughpu
Doesn't help reduce burden on lab techs
agarose assay is challenging to observe single-cell response
Not a deal-breaker as long as RA+ neutrophils are not activated
Among them, the Boyden chamber/transwell assay is the first and most broadly used che-motaxis assay. It is easy to perform and allows high-throughput experiments in parallel.However, this method only enables end-point analysis and thereby disallows the visualiza-tion of cell movement in real time
Could be useful, but also could activate RA+ neutrophils. Risky
This situation leadsto the application of human immortalizedleukemia cell lines HL-60and PLB-985, which can bedifferentiated into neutrophil-like cells (denoted as dHL-60 and dPLB-985 cells, respectively)
Not useful for our application --> want "normal" RA neutrophils.
Primary human neutrophils iso-lated from peripheral blood have a short half-life (12 h
Short half life is of some concern, but we hope to isolate the cells within an hour --> Less time is better to ease burden on lab techs.
igure 6. Effects of heterochromatin perturb
Perturbing balance to show that it still works even while perturbed First mention of mechanism
A) Time curves of the +1 insertion (red) and 7 deletion (blue) in s
Most significant shift is in triple heterochromatin structure. Prior triple heterochromatin presence is best indicator of NHEJ, but this figure shows that MMEJ doesn't happen as much/is over predicted
DISCUSSION
Take home messages: The chromatin landscape shifts prevalence between NHEJ and MMEJ
Total indel frequency at each IPR obtained withLBR2 sgRNA, split into different combinations ofheterochromatin features present, as indicated byblack dots in the scheme below the graph. Redlines show median values. Boxed numbers indi-cate the number of IPRs in each group; onlygroups with >20 IPRs are shown. Asterisks mark pvalues according to Wilcoxon test, compared witheuchromatin IPRs (leftmost column): *p < 0.05,**p < 0.01, ***p < 0.001, and ****p < 0.0001.(F) Same as (E) b
Look at specific chromatin features, F does the same, but shows that the mutations are still not random
D) Spearman’s correlations between total indelfrequencies in IPRs and the local intensities of 24chromatin features
Chromatin features and landscape Top ones show upregulation of transcription Bottom ones show downregulation of tumor suppressors
Scatterplots of total indel frequencies obtainedwith LBR2 versus the thre
Mutations correlate with each other, they are similar, not random
Figure 3. IPR total indel frequency varies asa function of chromatin contex
Important Figure
Indel frequencies of all IPRs shown in (A), 64 h after Cas9 induction. Dataare average of two to six independent replicates.See also Figures S1 and S2.
Shows the -7 and +1 indels again -> chromatin landscape
7 indels indeed represent NHEJ and MMEJ, respectively,we depleted or inhibited several pathway-specific proteins(Chang et al., 2017; Scully et al., 2019) in either the pools or clone5 ( Figure S2). The +1 insertion was strongly reduced, and the 7deletion was increased by inhibition of DNA-PKcs by the com-pounds NU7441 (Figures S2A and S2B) or M3814 (Figure
The -7 and +1 indel sizes are linked to chromatin landscape
K562 cells
Immortalized AML cell line Cell Line prefers NH over NHEJ All based on one cell line -> limitation, but advantage for deep dive
TRIP (thousandsof reporters integrated in parallel)
Definition of TRIP- Thousands of Reporters Integrated in Parallel
We in-serted the reporter sequence into a PiggyBac transposon vector,together with a 16 bp random barcode sequence that waslocated 56 bp from the DSB site (Figure 1B).
How to detect
relative activities
What type of DNA repair fixes each scar
multiplexedreporter assay in combination with Cas9 cutting
Causes "scars" across genome
BRCA1-mutated karyotyp
Lots of chromosomal translocations
Genetic signatures from Cbioporta
Melanoma: Nucleotide Excision Repair, Ovarian: dsDNA break
DNA DSB and cell cycle regulatio
HR is very cell-cycle dependent
PARPi changing the face of ovarian cancer
Paradigm changing, helps extend survivability with an oral medicine (can be administered at home)
ARP inhibitors and synthetic letha
Sense ssDNA break, keep PARP1 out, kill ovarian cancer cells via PARP trapping, stalls polymerase, causes dsDNA breaks, cannot be fixed with HR. Exploit genetic instability to kill cancer cells. Also leads to immune response
NHEJ and IgG/TCR generatio
Native use of NHEJ in VDJ recombination, leads to diversity in immune response --> highjacked by cancers to diversify oncogenome to select for increased fitness
hat is a major contributor to DNA adducts that result in BER?Familial adenomatosis- Mutation in MYH - Glycosylase- Colonic adenomasShortPatchRepairLong
Triggered by reactive oxygen species (ROS)
What is the result of MSI?- Gene level- Protein level
Consequences of high MSI mutational load, higher neoatigen load, better predictor of some cancers
icrosatellite – short, repeated sequences of DNA (Example: GTGTGTGTGT)- MSI – caused by deficiencies in repairing DNA mismatch repair (MMR) during DNA replication- MSI is considered a hypermutable phenotyp
Easy to mess up repeated sequences --> easy to mutate
Cancer syndromes related to DNA
Lots of cancer syndromes associated with DNA damage -> this is why DNA damage is important
DNA Repair Workflo
All DNA repair strategies must do these steps: Know this for knowing your repair pathways -> assessment
Sources of DNA Damage
Think of a decision making tree/flow chart
ROS, SAM, Natural IR: Most common, happens naturally
One resolution of these complexitiesmay come from functional assays ofthese disparate genes. An example ofsuch an assay is provided by the co-transfection test described above inwhich genes can be defined by theirability to help ras or myc to transformREF’s.
Instead of focusing on function of ras or myc, look at the effect of genes that cooperate with ras and myc
problematical: the ho-mologies are only vestigial
Problem is that homology is often vestigal: code for different sites
One measure of simplification comesfrom comparison of structures of thevarious genes and their encoded pro-teins. Structural homology often impliesfunctional analogy.
Structure denotes function
However, when the Ha-ras andmyc oncogene clones were applied to-gether to the REF cultures, dense foci ofmorphologically transformed cells werefound. Acting together, myc and raswere able to do what neither could do onits own.
Ras and myc alone are insufficient, but together cause tumorigenesis
While the ras gene alone be-haved like an incomplete oncogene, itwas clear that the two oncogenes togeth-er achieved complete conversion to tu-morigenicity.
Neither ras and Viral oncogenes induce tumorigenesis by themselves, but cooperate to induce tumorigenesis
These results bore on the issue ofmultistep carcinogenesis. They showedthat a single genetic alteration, such asone leading to creation of a ras onco-gene, was insufficient to achieve tumori-genic conversion of a normal fibroblast
Shows that single mutation is insufficient, need multiple mutations to induce tumorigenesis
The powers of this Ha-ras oncogenewere thus very limited when the genewas expressed within REF’s. However,if recipient cells used for transfectionhad been previously established and im-mortalized in culture, as was the casewith the rat-I (or NIH 3T3) cells, asubsequently introduced oncogene wasable to force the cells into a fully trans-formed, tumorigenic state in a singlestep. Stated differently, it appeared thatone consequence of establishing or im-mortalizing cells in culture was the acti-vation of cellular functions that couldcooperate with the ras gene to create thefull transformation phenotype.
RAS efficacy limited in REFs, but very effective in immortalized cells
ponded to transfection of the onco-gene by producing hundreds of foci un-der comparable conditions. These re-sults were not due to an inability of thetransfected gene to establish itselfwithinthe REF’s. Rather,
RAS doesn't work well by itself in Rat embryonic fibroblasts (REF)
Thecreation of a tumor cell within a tissuewould seem to require far more than theactivation of one of these oncogeneswithin the cell.
Tumorigenesis needs multiple mutations to succeed, especially for metastasis
his means that the N-ras and mycproto-oncogenes are susceptible to acti-vation in a variety of tissues.
Ras and myc are not tissue specific
alter-ation in the structure of the oncogeneprotein.
Fifth Mechanism: change the translated protein's structure
juxta-position of myc and immunoglobulin do-mains following chromosomal transloca-tion. This appears to result in deregula-tion ofthe myc gene,
Fourth Mechanism: Deregulation of myc gene.
A third mechanism influences levels oftranscription and, in turn, the amounts ofgene product.
Third Mechanism: Transcription is increased, increasing translation of proteins
verexpression due to amplifica-tion of the proto-oncogene or oncogene.
Second Mechanism: Overexpression because proto/oncogene is amplified
acquisition of a novel4transcriptional promoter.
First mechanism: Get a new promoter
erhaps the remaining 80 percentof the tumors harbor oncogenes thatrequire specialized recipient cells in or-der to register in a transfection focusassay.
Need to have specialized recipient cells to be detected in assay
Transfected Tumor Oncogenes
Second Type
Retrovirus-Associated Oncogenes
First type