Cancer genomic, transcriptomic, and proteomic profiling has generated extensive data that necessitate the development of tools for its analysis and dissemination. We developed UALCAN to provide a portal for easy exploring, analyzing, and visualizing these data, allowing users to integrate the data to better understand the gene, proteins, and pathways perturbed in cancer and make discoveries. UALCAN web portal enables analyzing and delivering cancer transcriptome, proteomics, and patient survival data to the cancer research community. With data obtained from The Cancer Genome Atlas (TCGA) project, UALCAN has enabled users to evaluate protein-coding gene expression and its impact on patient survival across 33 types of cancers. The web portal has been used extensively since its release and received immense popularity, underlined by its usage from cancer researchers in more than 100 countries. The present manuscript highlights the task we have undertaken and updates that we have made to UALCAN since its release in 2017. Extensive user feedback motivated us to expand the resource by including data on a) microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and promoter DNA methylation from TCGA and b) mass spectrometry-based proteomics from the Clinical Proteomic Tumor Analysis Consortium (CPTAC). UALCAN provides easy access to pre-computed, tumor subgroup-based gene/protein expression, promoter DNA methylation status, and Kaplan-Meier survival analyses. It also provides new visualization features to comprehend and integrate observations and aids in generating hypotheses for testing. UALCAN is accessible at http://ualcan.path.uab.edu
12 February 2020 in Science Translational Medicine
Women of sub-Saharan African descent have disproportionately higher incidence of triple-negative breast cancer (TNBC) and TNBC-specific mortality across all populations. Population studies show racial differences in TNBC biology, including higher prevalence of basal-like and quadruple-negative subtypes in African Americans (AA). However, previous investigations relied on self-reported race (SRR) of primarily U.S. populations. Due to heterogeneous genetic admixture and biological consequences of social determinants, the true association of African ancestry with TNBC biology is unclear. To address this, we conducted RNA sequencing on an international cohort of AAs, as well as West and East Africans with TNBC. Using comprehensive genetic ancestry estimation in this African-enriched cohort, we found expression of 613 genes associated with African ancestry and 2,000+ associated with regional African ancestry. A subset of African-associated genes also showed differences in normal breast tissue. Pathway enrichment and deconvolution of tumor cellular composition revealed that tumor-associated immunologic profiles are distinct in patients of African descent. Significance: Our comprehensive ancestry quantification process revealed that ancestry-associated gene expression profiles in TNBC include population-level distinctions in immunologic landscapes. These differences may explain some differences in race–group clinical outcomes. This study shows the first definitive link between African ancestry and the TNBC immunologic landscape, from an African-enriched international multiethnic cohort. See related commentary by Hamilton et al., p. 2496. This article is highlighted in the In This Issue feature, p. 2483
Rationally sequencing and combining PD-1/L1-and MAPK-targeted therapies may overcome innate and acquired resistance. Since increased clinical benefit of MAPK inhibitors (MAPKi) is associated with previous immune checkpoint therapy, we compare the efficacies of sequential and/or combinatorial regimens in subcutaneous murine models of melanoma driven by BrafV600, Nras, or Nf1 mutations as well as colorectal and pancreatic carcinoma driven by KrasG12C. Anti-PD-1/L1 lead-in preceding MAPKi combination optimizes response durability by promoting pro-inflammatory polarization of macrophages and clonal expansion of interferon-γhi, and CD8+ cytotoxic and proliferative (versus CD4+ regulatory) T cells that highly express activation genes. Since therapeutic resistance of melanoma brain metastasis (MBM) limits patient survival, we demonstrate that sequencing anti-PD-1/L1 therapy before MAPKi combination suppresses MBM and improves mouse survival with robust T cell clonal expansion in both intracranial and extracranial metastatic sites. We propose clinically testing brief anti-PD-1/L1 (± anti-CTLA-4) dosing before MAPKi co-treatment to suppress therapeutic resistance.
Purpose: Although, for patients with cancer, comorbidity can affect the timing of cancer detection, treatment, and prognosis, there is little information relating to the question of whether the choice of comorbidity index affects the results of studies. Therefore, to compare the association of comorbidity with mortality after surgery for colon cancer, this study evaluated the Adult Comorbidity Evaluation-27 (ACE-27), the National Institute on Aging (NIA) and National Cancer Institute (NCI) Comorbidity Index, and the Charlson Comorbidity Index (CCI). Patients and Methods: The study population consisted of colon cancer patients (N = 496) who underwent surgery at the University of Alabama at Birmingham Hospital from 1981 to 2002. Hazard ratios (HRs) with 95% CIs were obtained using the method of Cox proportional hazards for the three comorbidity indices in predicting overall and colon cancer–specific mortality. The point estimates obtained for comorbidity and other risk factors across the three models were compared. Results: For each index, the highest comorbidity burden was significantly associated with poorer overall survival (ACE-27: HR = 1.63; 95% CI, 1.24 to 2.15; NIA/NCI: HR = 1.83; 95% CI, 1.29 to 2.61; CCI: HR = 1.46; 95% CI, 1.14 to 1.88) as well as colon cancer–specific survival. For the other risk factors, there was little variation in the point estimates across the three models. Conclusion: The results obtained from these three indices were strikingly similar. For patients with severe comorbidity, all three indices were statistically significant in predicting shorter survival after surgery for colon cancer.