Pan-cancer proteogenomics connects oncogenic drivers to functional states.

Cancer driver events refer to key genetic aberrations that drive oncogenesis; however, their exact molecular mechanisms remain insufficiently understood. Here, our multi-omics pan-cancer analysis uncovers insights into the impacts of cancer drivers by identifying their significant cis-effects and distal trans-effects quantified at the RNA, protein, and phosphoprotein levels. Salient observations include the association of point mutations and copy-number alterations with the rewiring of protein interaction networks, and notably, most cancer genes converge toward similar molecular states denoted by sequence-based kinase activity profiles. A correlation between predicted neoantigen burden and measured T cell infiltration suggests potential vulnerabilities for immunotherapies. Patterns of cancer hallmarks vary by polygenic protein abundance ranging from uniform to heterogeneous. Overall, our work demonstrates the value of comprehensive proteogenomics in understanding the functional states of oncogenic drivers and their links to cancer development, surpassing the limitations of studying individual cancer types.

A proteogenomic portrait of lung squamous cell carcinoma.

Lung squamous cell carcinoma (LSCC) remains a leading cause of cancer death with few therapeutic options. We characterized the proteogenomic landscape of LSCC, providing a deeper exposition of LSCC biology with potential therapeutic implications. We identify NSD3 as an alternative driver in FGFR1-amplified tumors and low-p63 tumors overexpressing the therapeutic target survivin. SOX2 is considered undruggable, but our analyses provide rationale for exploring chromatin modifiers such as LSD1 and EZH2 to target SOX2-overexpressing tumors. Our data support complex regulation of metabolic pathways by crosstalk between post-translational modifications including ubiquitylation. Numerous immune-related proteogenomic observations suggest directions for further investigation. Proteogenomic dissection of CDKN2A mutations argue for more nuanced assessment of RB1 protein expression and phosphorylation before declaring CDK4/6 inhibition unsuccessful. Finally, triangulation between LSCC, LUAD, and HNSCC identified both unique and common therapeutic vulnerabilities. These observations and proteogenomics data resources may guide research into the biology and treatment of LSCC.

Single-Cell Discovery and Multiomic Characterization of Therapeutic Targets in Multiple Myeloma.

Multiple myeloma (MM) is a highly refractory hematologic cancer. Targeted immunotherapy has shown promise in MM but remains hindered by the challenge of identifying specific yet broadly representative tumor markers. We analyzed 53 bone marrow (BM) aspirates from 41 MM patients using an unbiased, high-throughput pipeline for therapeutic target discovery via single-cell transcriptomic profiling, yielding 38 MM marker genes encoding cell-surface proteins and 15 encoding intracellular proteins. Of these, 20 candidate genes were highlighted that are not yet under clinical study, 11 of which were previously uncharacterized as therapeutic targets. The findings were cross-validated using bulk RNA sequencing, flow cytometry, and proteomic mass spectrometry of MM cell lines and patient BM, demonstrating high overall concordance across data types. Independent discovery using bulk RNA sequencing reiterated top candidates, further affirming the ability of single-cell transcriptomics to accurately capture marker expression despite limitations in sample size or sequencing depth. Target dynamics and heterogeneity were further examined using both transcriptomic and immuno-imaging methods. In summary, this study presents a robust and broadly applicable strategy for identifying tumor markers to better inform the development of targeted cancer therapy. SIGNIFICANCE: Single-cell transcriptomic profiling and multiomic cross-validation to uncover therapeutic targets identifies 38 myeloma marker genes, including 11 transcribing surface proteins with previously uncharacterized potential for targeted antitumor therapy.

Differential chromatin accessibility and transcriptional dynamics define breast cancer subtypes and their lineages.

Breast cancer is a heterogeneous disease, and treatment is guided by biomarker profiles representing distinct molecular subtypes. Breast cancer arises from the breast ductal epithelium, and experimental data suggests breast cancer subtypes have different cells of origin within that lineage. The precise cells of origin for each subtype and the transcriptional networks that characterize these tumor-normal lineages are not established. In this work, we applied bulk, single-cell (sc), and single-nucleus (sn) multi-omic techniques as well as spatial transcriptomics and multiplex imaging on 61 samples from 37 breast cancer patients to show characteristic links in gene expression and chromatin accessibility between breast cancer subtypes and their putative cells of origin. We applied the PAM50 subtyping algorithm in tandem with bulk RNA-seq and snRNA-seq to reliably subtype even low-purity tumor samples and confirm promoter accessibility using snATAC. Trajectory analysis of chromatin accessibility and differentially accessible motifs clearly connected progenitor populations with breast cancer subtypes supporting the cell of origin for basal-like and luminal A and B tumors. Regulatory network analysis of transcription factors underscored the importance of BHLHE40 in luminal breast cancer and luminal mature cells, and KLF5 in basal-like tumors and luminal progenitor cells. Furthermore, we identify key genes defining the basal-like ( PRKCA , SOX6 , RGS6 , KCNQ3 ) and luminal A/B ( FAM155A , LRP1B ) lineages, with expression in both precursor and cancer cells and further upregulation in tumors. Exhausted CTLA4-expressing CD8+ T cells were enriched in basal-like breast cancer, suggesting altered means of immune dysfunction among breast cancer subtypes. We used spatial transcriptomics and multiplex imaging to provide spatial detail for key markers of benign and malignant cell types and immune cell colocation. These findings demonstrate analysis of paired transcription and chromatin accessibility at the single cell level is a powerful tool for investigating breast cancer lineage development and highlight transcriptional networks that define basal and luminal breast cancer lineages.

Comprehensive characterization of 536 patient-derived xenograft models prioritizes candidatesfor targeted treatment.

Development of candidate cancer treatments is a resource-intensive process, with the research community continuing to investigate options beyond static genomic characterization. Toward this goal, we have established the genomic landscapes of 536 patient-derived xenograft (PDX) models across 25 cancer types, together with mutation, copy number, fusion, transcriptomic profiles, and NCI-MATCH arms. Compared with human tumors, PDXs typically have higher purity and fit to investigate dynamic driver events and molecular properties via multiple time points from same case PDXs. Here, we report on dynamic genomic landscapes and pharmacogenomic associations, including associations between activating oncogenic events and drugs, correlations between whole-genome duplications and subclone events, and the potential PDX models for NCI-MATCH trials. Lastly, we provide a web portal having comprehensive pan-cancer PDX genomic profiles and source code to facilitate identification of more druggable events and further insights into PDXs' recapitulation of human tumors.

Uncommon non-oncogenic HPV genotypes, TP53 and MDM2 genes polymorphisms in HIV-infected women in Southern Brazil.

BACKGROUND: It is believed that Human Papillomavirus (HPV) and Human Immunodeficiency Virus coinfection contributes to increase the risk for cervical intraepithelial injuries. Several factors may contribute to cervical cancer (CC) development, including genetic variants such as TP53 and MDM2 gene polymorphisms. MATERIALS AND METHODS: A hundred HIV-infected women were examined for HPV detection and its genotypes, as well as the frequencies of the SNPs Arg72Pro and SNP309 and their associations with CC risk factors. Nested Polymerase Chain Reaction (nPCR) was used for HPV detection and PCR-RFLP for TP53 and MDM2 SNP309 genotyping. RESULTS: HPV DNA was detected in 68% of samples. A higher frequency of low-risk HPV genotypes (66.7%) was observed when compared to high-risk genotypes (33.3%). Nine different HPV genotypes were identified, with the highest prevalence of HPV-6, followed by HPV-16 and 31. p53 Arg72Arg and SNP309 TG genotype were the most prevalent. HPV genotyping was performed by sequencing. CONCLUSION: The data obtained suggest that HIV-infected women are more susceptible to be infected by low-risk HPV (LR-HPV) genotypes than by high-risk (HR-HPV), and Pro72Pro of TP53 gene and TG of MDM2 SNP309 genotypes apparently seem to be protective factors among HIV-infected women for HPV acquisition and HR-HPV infection, respectively, in a sample of Southern Brazilian woman. Future investigations in larger populations are necessary to better understand the potential roles of these SNPs and the behavior of non-oncogenic HPV genotypes in HIV-mediated immunosuppression cases.

Evidence for an epistatic effect between TP53 R72P and MDM2 T309G SNPs in HIV infection: a cross-sectional study in women from South Brazil.

OBJECTIVE: To investigate the associations of TP53 R72P and MDM2 T309G SNPs with HPV infection status, HPV oncogenic risk and HIV infection status. DESIGN: Cross-sectional study combining two groups (150 HIV-negative and 100 HIV-positive) of women. METHODS: Data was collected using a closed questionnaire. DNA was extracted from cervical samples. HPV infection status was determined by nested-PCR, and HPV oncogenic risk group by Sanger sequencing. Both SNPS were genotyped by PCR-RFLP. Crude and adjusted associations involving each exposure (R72P and T309G SNPs, as well as 13 models of epistasis) and each outcome (HPV status, HPV oncogenic risk group and HIV infection) were assessed using logistic regression. RESULTS: R72P SNP was protectively associated with HPV status (overdominant model), as well as T309G SNP with HPV oncogenic risk (strongest in the overdominant model). No epistatic model was associated with HPV status, but a dominant (R72P over T309G) protective epistatic effect was observed for HPV oncogenic risk. HIV status was strongly associated (risk factor) with different epistatic models, especially in models based on a visual inspection of the results. Moreover, HIV status was evidenced to be an effect mediator of the associations involving HPV oncogenic risk. CONCLUSIONS: We found evidence for a role of R72P and T309G SNPs in HPV status and HPV oncogenic risk (respectively), and strong associations were found for an epistatic effect in HIV status. Prospective studies in larger samples are warranted to validate our findings, which point to a novel role of these SNPs in HIV infection.

Uncommon non-oncogenic HPV genotypes, TP53 and MDM2 genes polymorphisms in HIV-infected women in Southern Brazil

Background: It is believed that Human Papillomavirus (HPV) and Human Immunodeficiency Virus coinfection contributes to increase the risk for cervical intraepithelial injuries. Several factors may contribute to cervical cancer (CC) development, including genetic variants such as TP53 and MDM2 gene polymorphisms. Materials and methods: A hundred HIV-infected women were examined for HPV detection and its genotypes, as well as the frequencies of the SNPs Arg72Pro and SNP309 and their associations with CC risk factors. Nested Polymerase Chain Reaction (nPCR) was used for HPV detection and PCR-RFLP for TP53 and MDM2 SNP309 genotyping. Results: HPV DNA was detected in 68% of samples. A higher frequency of low-risk HPV genotypes (66.7%) was observed when compared to high-risk genotypes (33.3%). Nine different HPV genotypes were identified, with the highest prevalence of HPV-6, followed by HPV-16 and 31. p53 Arg72Arg and SNP309 TG genotype were the most prevalent. HPV genotyping was performed by sequencing. Conclusion: The data obtained suggest that HIV-infected women are more susceptible to be infected by low-risk HPV (LR-HPV) genotypes than by high-risk (HR-HPV), and Pro72Pro of TP53 gene and TG of MDM2 SNP309 genotypes apparently seem to be protective factors among HIV-infected women for HPV acquisition and HR-HPV infection, respectively, in a sample of Southern Brazilian woman. Future investigations in larger populations are necessary to better understand the potential roles of these SNPs and the behavior of non-oncogenic HPV genotypes in HIV-mediated immunosuppression cases. .