Comprehensive Clinical and Molecular Characterization of KRASG12C-Mutant Colorectal Cancer

PURPOSE KRAS p.G12C mutations occur in approximately 3% of metastatic colorectal cancers (mCRC). Recently, two allosteric inhibitors of KRAS p.G12C have demonstrated activity in early phase clinical trials. There are no robust studies examining the behavior of this newly targetable population. METHODS We queried the MD Anderson Cancer Center data set for patients with colorectal cancer who harbored KRAS p.G12C mutations between January 2003 and September 2019. Patients were analyzed for clinical characteristics, overall survival (OS), and progression-free survival (PFS) and compared against KRAS nonG12C. Next, we analyzed several internal and external data sets to assess immune signatures, gene expression profiles, hypermethylation, co-occurring mutations, and proteomics. RESULTS Among the 4,632 patients with comprehensive molecular profiling, 134 (2.9%) were found to have KRAS p.G12C mutations. An additional 53 patients with single gene sequencing were included in clinical data but excluded from prevalence analysis allowing for 187 total patients. Sixty-five patients had de novo metastatic disease and received a median of two lines of chemotherapy without surgical intervention. For the first three lines of chemotherapy, the median PFS was 6.4 months (n = 65; 95% CI, 5.0 to 7.4 months), 3.9 months (n = 47; 95% CI, 2.9 to 5.9 months), and 3.0 months (n = 21; 95% CI, 2.0 to 3.4 months), respectively. KRAS p.G12C demonstrated higher rates of basal EGFR activation compared with KRAS nonG12C. When compared with an internal cohort of KRAS nonG12C, KRAS p.G12C patients had worse OS. CONCLUSION PFS is poor for patients with KRAS p.G12C metastatic colorectal cancer. OS was worse in KRAS p.G12C compared with KRAS nonG12C patients. Our data highlight the innate resistance to chemotherapy for KRAS p.G12C patients and serve as a historical comparator for future clinical trials.

Download Full-text

Adipose transcriptome analysis provides novel insights into molecular regulation of prolonged fasting in northern elephant seal pups

Physiological Genomics ◽

10.1152/physiolgenomics.00002.2018 ◽

2018 ◽

Vol 50 (7) ◽

pp. 495-503 ◽

Cited By ~ 6

Author(s):

Bridget Martinez ◽

Jane Khudyakov ◽

Kim Rutherford ◽

Daniel E. Crocker ◽

Neil Gemmell ◽

...

Keyword(s):

Marine Mammals ◽

Energy Homeostasis ◽

De Novo ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Global Gene Expression ◽

Elephant Seal ◽

Prolonged Fasting ◽

Northern Elephant Seal ◽

Data Set

The physiological and cellular adaptations to extreme fasting in northern elephant seals ( Mirounga angustirostris, NES) are remarkable and may help to elucidate endocrine mechanisms that regulate lipid metabolism and energy homeostasis in mammals. Recent studies have highlighted the importance of thyroid hormones in the maintenance of a lipid-based metabolism during prolonged fasting in weaned NES pups. To identify additional molecular regulators of fasting, we used a transcriptomics approach to examine changes in global gene expression profiles before and after 6–8 wk of fasting in weaned NES pups. We produced a de novo assembly and identified 98 unique protein-coding genes that were differentially expressed between early and late fasting. Most of the downregulated genes were associated with lipid, carbohydrate, and protein metabolism. A number of downregulated genes were also associated with maintenance of the extracellular matrix, consistent with tissue remodeling during weight loss and the multifunctional nature of blubber tissue, which plays both metabolic and structural roles in marine mammals. Using this data set, we predict potential mechanisms by which NES pups sustain metabolism and regulate adipose stores throughout the fast, and provide a valuable resource for additional studies of extreme metabolic adaptations in mammals.

Download Full-text

Metastatic heterogeneity of the consensus molecular subtypes of colorectal cancer

npj Genomic Medicine ◽

10.1038/s41525-021-00223-7 ◽

2021 ◽

Vol 6 (1) ◽

Author(s):

Peter W. Eide ◽

Seyed H. Moosavi ◽

Ina A. Eilertsen ◽

Tuva H. Brunsell ◽

Jonas Langerud ◽

...

Keyword(s):

Gene Expression ◽

Colorectal Cancer ◽

Principal Components ◽

Prognostic Value ◽

Tumor Heterogeneity ◽

Molecular Subtypes ◽

R Package ◽

Data Set ◽

Primary Tumors ◽

External Data

AbstractGene expression-based subtypes of colorectal cancer have clinical relevance, but the representativeness of primary tumors and the consensus molecular subtypes (CMS) for metastatic cancers is not well known. We investigated the metastatic heterogeneity of CMS. The best approach to subtype translation was delineated by comparisons of transcriptomic profiles from 317 primary tumors and 295 liver metastases, including multi-metastatic samples from 45 patients and 14 primary-metastasis sets. Associations were validated in an external data set (n = 618). Projection of metastases onto principal components of primary tumors showed that metastases were depleted of CMS1-immune/CMS3-metabolic signals, enriched for CMS4-mesenchymal/stromal signals, and heavily influenced by the microenvironment. The tailored CMS classifier (available in an updated version of the R package CMScaller) therefore implemented an approach to regress out the liver tissue background. The majority of classified metastases were either CMS2 or CMS4. Nonetheless, subtype switching and inter-metastatic CMS heterogeneity were frequent and increased with sampling intensity. Poor-prognostic value of CMS1/3 metastases was consistent in the context of intra-patient tumor heterogeneity.

Download Full-text

Gene Expression Profiles as Predictors of Poor Outcomes in Stage II Colorectal Cancer: A Systematic Review and Meta-analysis

Clinical Colorectal Cancer ◽

10.3816/ccc.2009.n.035 ◽

2009 ◽

Vol 8 (4) ◽

pp. 207-214 ◽

Cited By ~ 22

Author(s):

An-Ting T. Lu ◽

Shelley R. Salpeter ◽

Anthony E. Reeve ◽

Steven Eschrich ◽

Patrick G. Johnston ◽

...

Keyword(s):

Gene Expression ◽

Colorectal Cancer ◽

Systematic Review ◽

Expression Profiles ◽

Meta Analysis ◽

Gene Expression Profiles ◽

Stage Ii ◽

Stage Ii Colorectal Cancer ◽

Poor Outcomes

Download Full-text

Integrative Genomics with Mediation Analysis in a Survival Context

Computational and Mathematical Methods in Medicine ◽

10.1155/2013/413783 ◽

2013 ◽

Vol 2013 ◽

pp. 1-8 ◽

Cited By ~ 2

Author(s):

Szilárd Nemes ◽

Toshima Z. Parris ◽

Anna Danielsson ◽

Zakaria Einbeigi ◽

Gunnar Steineck ◽

...

Keyword(s):

Expression Profiles ◽

Gene Expression Profiles ◽

Genomic Analysis ◽

Mrna Levels ◽

Integrative Genomics ◽

Asymptotic Results ◽

Data Set ◽

Cancer Data ◽

Dna And Rna ◽

Altered Gene

DNA copy number aberrations (DCNA) and subsequent altered gene expression profiles may have a major impact on tumor initiation, on development, and eventually on recurrence and cancer-specific mortality. However, most methods employed in integrative genomic analysis of the two biological levels, DNA and RNA, do not consider survival time. In the present note, we propose the adoption of a survival analysis-based framework for the integrative analysis of DCNA and mRNA levels to reveal their implication on patient clinical outcome with the prerequisite that the effect of DCNA on survival is mediated by mRNA levels. The specific aim of the paper is to offer a feasible framework to test the DCNA-mRNA-survival pathway. We provide statistical inference algorithms for mediation based on asymptotic results. Furthermore, we illustrate the applicability of the method in an integrative genomic analysis setting by using a breast cancer data set consisting of 141 invasive breast tumors. In addition, we provide implementation in R.

Download Full-text

Differential expression of sarcospan in human epithelial ovarian cancer.

10.31219/osf.io/k4ceq ◽

2021 ◽

Author(s):

Shahan Mamoor

Keyword(s):

Ovarian Cancer ◽

Epithelial Ovarian Cancer ◽

Fallopian Tube ◽

Expression Profiles ◽

Gynecologic Cancer ◽

Gene Expression Profiles ◽

Progression Free Survival ◽

High Grade ◽

Primary Tumors ◽

Ovarian Cancers

Epithelial ovarian cancer (EOC) is the most lethal gynecologic cancer (1). We performed discovery of genes associated with epithelial ovarian cancer and of the high-grade serous ovarian cancer (HGSC) subtype, using published microarray data (2, 3) to compare global gene expression profiles of normal ovary or fallopian tube with that of primary tumors from women diagnosed with epithelial ovarian cancer or HGSC. We identified the gene encoding sarcospan, SSPN, as among the genes whose expression was most different in epithelial ovarian cancer as compared to the normal fallopian tube. SSPN expression was significantly lower in high-grade serous ovarian tumors relative to normal fallopian tube. SSPN expression correlated with progression-free survival in patients with ovarian cancer. These data indicate that expression of SSPN is perturbed in epithelial ovarian cancers broadly and in ovarian cancers of the HGSC subtype. SSPN may be relevant to pathways underlying ovarian cancer initiation (transformation) or progression.

Download Full-text

Differential expression of phosphodiesterase 5A in human epithelial ovarian cancer.

10.31219/osf.io/3jkpe ◽

2021 ◽

Author(s):

Shahan Mamoor

Keyword(s):

Ovarian Cancer ◽

Epithelial Ovarian Cancer ◽

Fallopian Tube ◽

Expression Profiles ◽

Gynecologic Cancer ◽

Gene Expression Profiles ◽

Progression Free Survival ◽

High Grade ◽

Primary Tumors ◽

Ovarian Cancers

Epithelial ovarian cancer (EOC) is the most lethal gynecologic cancer (1). We performed discovery of genes associated with epithelial ovarian cancer and of the high-grade serous ovarian cancer (HGSC) subtype, using published microarray data (2, 3) to compare global gene expression profiles of normal ovary or fallopian tube with that of primary tumors from women diagnosed with epithelial ovarian cancer or HGSC. We identified the gene encoding phosphodiesterase 5A, PDE5A, as among the genes whose expression was most different in epithelial ovarian cancer as compared to the normal fallopian tube. PDE5A expression was significantly lower in high-grade serous ovarian tumors relative to normal fallopian tube. PDE5A expression correlated with progression-free survival in patients with p53 mutant ovarian cancer. These data indicate that expression of PDE5A is perturbed in epithelial ovarian cancers broadly and in ovarian cancers of the HGSC subtype. PDE5A may be relevant to pathways underlying ovarian cancer initiation (transformation) or progression.

Download Full-text

Improved Feature Selection by Incorporating Gene Similarity into the LASSO

International Journal of Knowledge Discovery in Bioinformatics ◽

10.4018/jkdb.2012010101 ◽

2012 ◽

Vol 3 (1) ◽

pp. 1-22 ◽

Cited By ~ 1

Author(s):

Christopher E. Gillies ◽

Xiaoli Gao ◽

Nilesh V. Patel ◽

Mohammad-Reza Siadat ◽

George D. Wilson

Keyword(s):

Gene Expression ◽

Feature Selection ◽

Personalized Medicine ◽

Objective Function ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Genetic Profile ◽

Data Set ◽

Coordinate Descent Algorithm ◽

Gene Similarity

Personalized medicine is customizing treatments to a patient’s genetic profile and has the potential to revolutionize medical practice. An important process used in personalized medicine is gene expression profiling. Analyzing gene expression profiles is difficult, because there are usually few patients and thousands of genes, leading to the curse of dimensionality. To combat this problem, researchers suggest using prior knowledge to enhance feature selection for supervised learning algorithms. The authors propose an enhancement to the LASSO, a shrinkage and selection technique that induces parameter sparsity by penalizing a model’s objective function. Their enhancement gives preference to the selection of genes that are involved in similar biological processes. The authors’ modified LASSO selects similar genes by penalizing interaction terms between genes. They devise a coordinate descent algorithm to minimize the corresponding objective function. To evaluate their method, the authors created simulation data where they compared their model to the standard LASSO model and an interaction LASSO model. The authors’ model outperformed both the standard and interaction LASSO models in terms of detecting important genes and gene interactions for a reasonable number of training samples. They also demonstrated the performance of their method on a real gene expression data set from lung cancer cell lines.

Download Full-text

PCA-based unsupervised feature extraction for gene expression analysis of COVID-19 patients

Scientific Reports ◽

10.1038/s41598-021-95698-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Kota Fujisawa ◽

Mamoru Shimo ◽

Y.-H. Taguchi ◽

Shinya Ikematsu ◽

Ryota Miyata

Keyword(s):

Gene Expression ◽

Feature Extraction ◽

Target Genes ◽

Gene Selection ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Principal Component ◽

Data Set ◽

Immune Related Genes ◽

Unsupervised Feature Extraction

AbstractCoronavirus disease 2019 (COVID-19) is raging worldwide. This potentially fatal infectious disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the complete mechanism of COVID-19 is not well understood. Therefore, we analyzed gene expression profiles of COVID-19 patients to identify disease-related genes through an innovative machine learning method that enables a data-driven strategy for gene selection from a data set with a small number of samples and many candidates. Principal-component-analysis-based unsupervised feature extraction (PCAUFE) was applied to the RNA expression profiles of 16 COVID-19 patients and 18 healthy control subjects. The results identified 123 genes as critical for COVID-19 progression from 60,683 candidate probes, including immune-related genes. The 123 genes were enriched in binding sites for transcription factors NFKB1 and RELA, which are involved in various biological phenomena such as immune response and cell survival: the primary mediator of canonical nuclear factor-kappa B (NF-κB) activity is the heterodimer RelA-p50. The genes were also enriched in histone modification H3K36me3, and they largely overlapped the target genes of NFKB1 and RELA. We found that the overlapping genes were downregulated in COVID-19 patients. These results suggest that canonical NF-κB activity was suppressed by H3K36me3 in COVID-19 patient blood.

Download Full-text

The effects of a globin blocker on the resolution of 3’mRNA sequencing data in porcine blood

BMC Genomics ◽

10.1186/s12864-019-6122-2 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 1

Author(s):

Kyu-Sang Lim ◽

Qian Dong ◽

Pamela Moll ◽

Jana Vitkovska ◽

Gregor Wiktorin ◽

...

Keyword(s):

Gene Expression ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Data Sets ◽

Globin Genes ◽

Sequencing Data ◽

Globin Mrna ◽

Data Set ◽

Mrna Sequencing ◽

Porcine Blood

Abstract Background Gene expression profiling in blood is a potential source of biomarkers to evaluate or predict phenotypic differences between pigs but is expensive and inefficient because of the high abundance of globin mRNA in porcine blood. These limitations can be overcome by the use of QuantSeq 3’mRNA sequencing (QuantSeq) combined with a method to deplete or block the processing of globin mRNA prior to or during library construction. Here, we validated the effectiveness of QuantSeq using a novel specific globin blocker (GB) that is included in the library preparation step of QuantSeq. Results In data set 1, four concentrations of the GB were applied to RNA samples from two pigs. The GB significantly reduced the proportion of globin reads compared to non-GB (NGB) samples (P = 0.005) and increased the number of detectable non-globin genes. The highest evaluated concentration (C1) of the GB resulted in the largest reduction of globin reads compared to the NGB (from 56.4 to 10.1%). The second highest concentration C2, which showed very similar globin depletion rates (12%) as C1 but a better correlation of the expression of non-globin genes between NGB and GB (r = 0.98), allowed the expression of an additional 1295 non-globin genes to be detected, although 40 genes that were detected in the NGB sample (at a low level) were not present in the GB library. Concentration C2 was applied in the rest of the study. In data set 2, the distribution of the percentage of globin reads for NGB (n = 184) and GB (n = 189) samples clearly showed the effects of the GB on reducing globin reads, in particular for HBB, similar to results from data set 1. Data set 3 (n = 84) revealed that the proportion of globin reads that remained in GB samples was significantly and positively correlated with the reticulocyte count in the original blood sample (P < 0.001). Conclusions The effect of the GB on reducing the proportion of globin reads in porcine blood QuantSeq was demonstrated in three data sets. In addition to increasing the efficiency of sequencing non-globin mRNA, the GB for QuantSeq has an advantage that it does not require an additional step prior to or during library creation. Therefore, the GB is a useful tool in the quantification of whole gene expression profiles in porcine blood.

Download Full-text