Isoform specific gene expression analysis of KRAS in the prognosis of lung adenocarcinoma patients

Dividing out quantification uncertainty allows efficient assessment of differential transcript expression with edgeR

Differential expression analysis of RNA-seq is one of the most commonly performed bioinformatics analyses. Transcript-level quantifications are inherently more uncertain than gene-level read counts because of ambiguous assignment of sequence reads to transcripts. While sequence reads can usually be assigned unambiguously to a gene, reads are very often compatible with multiple transcripts for that gene, particularly for genes with many isoforms. Software tools designed for gene-level differential expression do not perform optimally on transcript counts because the read-to-transcript ambiguity (RTA) disrupts the mean-variance relationship normally observed for gene level RNA-seq data and interferes with the efficiency of the empirical Bayes dispersion estimation procedures. The pseudoaligners kallisto and Salmon provide bootstrap samples from which quantification uncertainty can be assessed. We show that the overdispersion arising from RTA can be elegantly estimated by fitting a quasi-Poisson model to the bootstrap counts for each transcript. The technical overdispersion arising from RTA can then be divided out of the transcript counts, leading to scaled counts that can be input for analysis by established gene-level software tools with full statistical efficiency. Comprehensive simulations and test data show that an edgeR analysis of the scaled counts is more powerful and efficient than previous differential transcript expression pipelines while providing correct control of the false discovery rate. Simulations explore a wide range of scenarios including the effects of paired vs single-end reads, different read lengths and different numbers of replicates.

KRAS4A and KRAS4B in liquid biopsy of metastatic lung adenocarcinoma patients treated with Pembrolizumab or chemotherapy plus Pembrolizumab

KRAS is involved in the stability and expression of PD-L1. We investigated the expression of circulating mRNA (cmRNA) of KRAS4A and KRAS4B and the possible impact on progression-free survival (PFS) of patients with metastatic lung adenocarcinoma treated with immunotherapy. Patients without driver mutations undergoing Pembrolizumab (P) or P plus chemotherapy (PC) were prospectively accrued for liquid biopsy analysis of KRAS4A, KRAS4B, and PD-L1 cmRNA. Both KRAS isoforms were also studied for association with PD-L1 cmRNA. Of 56 patients, 28 received P and 28 PC. Patients with high levels of both KRAS isoforms showed significantly better PFS. The median PFS for KRAS4A was 29 months (95% CI 22-29 months) and KRAS4B 24 months (95% CI 13-29 months), respectively. The median PFS of patients with low levels of both isoforms was 12 months (95% CI 6-15 months for KRAS4A and 95% CI 5-20 months for KRAS4B). High KRAS4A retained a significant positive association with PFS in the multivariate model. An exploratory analysis in treatment subgroups found a positive association between high KRAS4A and KRAS4B with PFS in patients treated with P. PD-L1 cmRNA was significantly higher in patients with high KRAS isoforms levels and this effect was pronounced for high KRAS4A carriers. KRAS4A deserves further investigation as a potential marker for defining patients who may benefit the most from immune checkpoint inhibitors therapy and improving personalized cancer immunotherapeutic strategies.

RNA splicing alterations in lung cancer pathogenesis and therapy

RNA splicing alterations are widespread and play critical roles in cancer pathogenesis and therapy. Lung cancer is highly heterogeneous and causes the most cancer-related deaths worldwide. Large-scale multi-omics studies have not only characterized the mutational landscapes but also discovered a plethora of transcriptional and post-transcriptional changes in lung cancer. Such resources have greatly facilitated the development of new diagnostic markers and therapeutic options over the past two decades. Intriguingly, altered RNA splicing has emerged as an important molecular feature and therapeutic target of lung cancer. In this review, we provide a brief overview of splicing dysregulation in lung cancer and summarize the recent progress on key splicing events and splicing factors that contribute to lung cancer pathogenesis. Moreover, we describe the general strategies targeting splicing alterations in lung cancer and highlight the potential of combining splicing modulation with currently approved therapies to combat this deadly disease. This review provides new mechanistic and therapeutic insights into splicing dysregulation in cancer.

The role of KRAS splice variants in cancer biology

The three mammalian RAS genes (HRAS, NRAS and KRAS) encode four proteins that play central roles in cancer biology. Among them, KRAS is mutated more frequently in human cancer than any other oncogene. The pre-mRNA of KRAS is alternatively spliced to give rise to two products, KRAS4A and KRAS4B, which differ in the membrane targeting sequences at their respective C-termini. Notably, both KRAS4A and KRAS4B are oncogenic when KRAS is constitutively activated by mutation in exon 2 or 3. Whereas KRAS4B is the most studied oncoprotein, KRAS4A is understudied and until recently considered relatively unimportant. Emerging work has confirmed expression of KRAS4A in cancer and found non-overlapping functions of the splice variants. The most clearly demonstrated of these is direct regulation of hexokinase 1 by KRAS4A, suggesting that the metabolic vulnerabilities of KRAS-mutant tumors may be determined in part by the relative expression of the splice variants. The aim of this review is to address the most relevant characteristics and differential functions of the KRAS splice variants as they relate to cancer onset and progression.

KRAS and MET in non-small-cell lung cancer: two of the new kids on the 'drivers' block

Non-small-cell lung cancer (NSCLC) is a heterogeneous disease, and therapeutic management has advanced to identify various critical oncogenic mutations that promote lung cancer tumorigenesis. Subsequent studies have developed targeted therapies against these oncogenes in the hope of personalized treatment based on the tumor's molecular genomics. This review presents a comprehensive review of the biology, new therapeutic interventions, and resistance patterns of two well-defined subgroups, tumors with KRAS and MET alterations. We also discuss the status of molecular testing practices for these two key oncogenic drivers, considering the progressive introduction of next-generation sequencing (NGS) and RNA sequencing in regular clinical practice.

A promising prognostic signature for lung adenocarcinoma (LUAD) patients basing on 6 hypoxia-related genes

BACKGROUND

Hypoxia signaling plays a critical role in the development of lung adenocarcinoma (LUAD). We herein aimed to explore the prognostic value of hypoxia-related genes and construct the hypoxia-related prognostic signature for LUAD patients.

METHODS

A total of 26 hypoxia-related genes were collected. Five hundred thirteen and 246 LUAD samples were obtained from the Cancer Genome Atlas and Gene Expression Omnibus databases, respectively. Univariate Cox regression and LASSO Cox regression analyses were conducted to screen the hypoxia-related genes associated with the prognosis of LUAD patients, which would be used for constructing prognosis predictive model for LUAD patients. Multivariate Cox regression analysis was done to determine the independent prognostic factors. The Nomogram model was constructed to predict the prognosis of LUAD patients.

RESULTS

Based on 26 hypoxia-related genes, LUAD samples could be divided into 4 clusters with different prognoses. Among which, 6 genes were included to construct the Risk Score and the LUAD patients with higher Risk Score had worse prognosis. Besides, the Nomogram based on all the independent risk factors could relatively reliably predict the survival probability. And 9 types of immune cells' infiltration was significantly differential between high and low risk LUAD patients.

CONCLUSION

The Risk Score model based on the 6 crucial hypoxia-related genes could relatively reliably predict the prognosis of LUAD patients.

Anticancer drug resistance: An update and perspective

Driver mutations promote initiation and progression of cancer. Pharmacological treatment can inhibit the action of the mutant protein; however, drug resistance almost invariably emerges. Multiple studies revealed that cancer drug resistance is based upon a plethora of distinct mechanisms. Drug resistance mutations can occur in the same protein or in different proteins; as well as in the same pathway or in parallel pathways, bypassing the intercepted signaling. The dilemma that the clinical oncologist is facing is that not all the genomic alterations as well as alterations in the tumor microenvironment that facilitate cancer cell proliferation are known, and neither are the alterations that are likely to promote metastasis. For example, the common KRasG12C driver mutation emerges in different cancers. Most occur in NSCLC, but some occur, albeit to a lower extent, in colorectal cancer and pancreatic ductal carcinoma. The responses to KRasG12C inhibitors are variable and fall into three categories, (i) new point mutations in KRas, or multiple copies of KRAS G12C which lead to higher expression level of the mutant protein; (ii) mutations in genes other than KRAS; (iii) original cancer transitioning to other cancer(s). Resistance to adagrasib, an experimental antitumor agent exerting its cytotoxic effect as a covalent inhibitor of the G12C KRas, indicated that half of the cases present multiple KRas mutations as well as allele amplification. Redundant or parallel pathways included MET amplification; emerging driver mutations in NRAS, BRAF, MAP2K1, and RET; gene fusion events in ALK, RET, BRAF, RAF1, and FGFR3; and loss-of-function mutations in NF1 and PTEN tumor suppressors. In the current review we discuss the molecular mechanisms underlying drug resistance while focusing on those emerging to common targeted cancer drivers. We also address questions of why cancers with a common driver mutation are unlikely to evolve a common drug resistance mechanism, and whether one can predict the likely mechanisms that the tumor cell may develop. These vastly important and tantalizing questions in drug discovery, and broadly in precision medicine, are the focus of our present review. We end with our perspective, which calls for target combinations to be selected and prioritized with the help of the emerging massive compute power which enables artificial intelligence, and the increased gathering of data to overcome its insatiable needs.

Cancer DEIso: An integrative analysis platform for investigating differentially expressed gene-level and isoform-level human cancer markers

Transcript isoforms regulated by alternative splicing can substantially impact carcinogenesis, leading to a need to obtain clues for both gene differential expression and malfunctions of isoform distributions in cancer studies. The Cancer Genome Atlas (TCGA) project was launched in 2008 to collect cancer-related genome mutation raw data from the population. While many repositories tried to add insights into the raw data in TCGA, no existing database provides both comprehensive gene-level and isoform-level cancer stage marker investigation and survival analysis. We constructed Cancer DEIso to facilitate in-depth analyses for both gene-level and isoform-level human cancer studies. Patient RNA-seq data, sample sheets, patient clinical data, and human genome datasets were collected and processed in Cancer DEIso. And four functions to search differentially expressed genes/isoforms between cancer stages were implemented: (i) Search potential gene/isoform markers for a specified cancer type and its two stages; (ii) Search potentially induced cancer types and stages for a gene/isoform; (iii) Expression survival analysis on a given gene/isoform for some cancer; (iv) Gene/isoform stage expression comparison visualization. As an example, we demonstrate that Cancer DEIso can indicate potential colorectal cancer isoform diagnostic markers that are not easily detected when only gene-level expressions are considered. Cancer DEIso is available at http://cosbi4.ee.ncku.edu.tw/DEIso/.

Ras isoform-specific expression, chromatin accessibility, and signaling

The anchorage of Ras isoforms in the membrane and their nanocluster formations have been studied extensively, including their detailed interactions, sizes, preferred membrane environments, chemistry, and geometry. However, the staggering challenge of their epigenetics and chromatin accessibility in distinct cell states and types, which we propose is a major factor determining their specific expression, still awaits unraveling. Ras isoforms are distinguished by their C-terminal hypervariable region (HVR) which acts in intracellular transport, regulation, and membrane anchorage. Here, we review some isoform-specific activities at the plasma membrane from a structural dynamic standpoint. Inspired by physics and chemistry, we recognize that understanding functional specificity requires insight into how biomolecules can organize themselves in different cellular environments. Within this framework, we suggest that isoform-specific expression may largely be controlled by the chromatin density and physical compaction, which allow (or curb) access to "chromatinized DNA." Genes are preferentially expressed in tissues: proteins expressed in pancreatic cells may not be equally expressed in lung cells. It is the rule-not an exception, and it can be at least partly understood in terms of chromatin organization and accessibility state. Genes are expressed when they can be sufficiently exposed to the transcription machinery, and they are less so when they are persistently buried in dense chromatin. Notably, chromatin accessibility can similarly determine expression of drug resistance genes.

Transcriptome Based Estrogen Related Genes Biomarkers for Diagnosis and Prognosis in Non-small Cell Lung Cancer

Background

Lung cancer is the tumor with the highest morbidity and mortality, and has become a global public health problem. The incidence of lung cancer in men has declined in some countries and regions, while the incidence of lung cancer in women has been slowly increasing. Therefore, the aim is to explore whether estrogen-related genes are associated with the incidence and prognosis of lung cancer.

Methods

We obtained all estrogen receptor genes and estrogen signaling pathway genes in The Cancer Genome Atlas (TCGA), and then compared the expression of each gene in tumor tissues and adjacent normal tissues for lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) separately. Survival analysis was performed of the differentially expressed genes in LUAD and LUSC patients separately. The diagnostic and prognostic values of the candidate genes were validated in the Gene Expression Omnibus (GEO) datasets.

Results

We found 5 estrogen receptor genes and 66 estrogen pathway genes in TCGA. A total of 50 genes were differently expressed between tumor tissues and adjacent normal tissues and 6 of the 50 genes were related to the prognosis of LUAD in TCGA. 56 genes were differently expressed between tumor tissues and adjacent normal tissues and none of the 56 genes was related to the prognosis of LUSC in TCGA. GEO datasets validated that the 6 genes (SHC1, FKBP4, NRAS, PRKCD, KRAS, ADCY9) had different expression between tumor tissues and adjacent normal tissues in LUAD, and 3 genes (FKBP4, KRAS, ADCY9) were related to the prognosis of LUAD.

Conclusions

The expressions of FKBP4 and ADCY9 are related to the pathogenesis and prognosis of LUAD. FKBP4 and ADCY9 may serve as biomarkers in LUAD screening and prognosis prediction in clinical settings.

Utility of KRAS Gene and Clinicopathological Features in the Assessment of the Risk of Type 2 Diabetes in the Etiology of Colon Cancer

Background  Cancer and diabetes have a tremendous impact on health globally. This study aimed to evaluate the KRAS gene in colon cancer tissues obtained from patients with type 2 diabetes mellitus (T2DM). Materials and Methods  Data from 315 cases (156 colon diabetics and 159 patients were nondiabetics) were retrospectively retrieved. mRNA from surgically resected colon cancer tumors were also retrieved. Results  The expression of KRAS mRNA was significantly higher in patients afflicted with T2DM than nondiabetic patients. The KRAS mRNA levels were significantly amplified from primary to metastatic lesions ( p  < 0.001). Conclusion  The association between T2DM and colon cancer was well-established in the present study.

Systematic assessment of the clinicopathological prognostic significance of tissue cytokine expression for lung adenocarcinoma based on integrative analysis of TCGA data

Dysregulated intratumoral immune reactions are shaped by complex networks of cytokines, which coordinate with tumor cells to determine tumor progression and aggressiveness. In lung adenocarcinoma (LUAD), the role of intratumoral cytokine gene expression for stratifying prognosis has not been systematically investigated. Using high-dimensional datasets of cancer specimens from clinical patients in The Cancer Genome Atlas (TCGA), we explored the transcript abundance and prognostic impact of 27 clinically evaluable cytokines in 500 LUAD tumor samples according to clinicopathological features and two common driver mutations (EGFR and KRAS). We found that reduced expression of IL12B presented as the single prognostic factor for both poor overall survival (OS) and recurrence free survival (RFS) with high hazard ratios. Moreover, we identified that elevated expression of IL6, CXCL8 and CSF3 were additional independent predictors of poor RFS in LUAD patients. Their prognostic significance was further strengthened by their ability to stratify within clinicopathological factors. Notably, we prioritized high risk cytokines for patients with or without mutations in EGFR and KRAS. Our results provide integrative associations of cytokine gene expression with patient survival and tumor recurrence and demonstrate the necessity and validity of relating clinicopathological and genetic disposition factors for precise and personalized disease prognosis.

Distribution of KRAS, DDR2, and TP53 gene mutations in lung cancer: An analysis of Iranian patients

Purpose

Lung cancer is the deadliest known cancer in the world, with the highest number of mutations in proto-oncogenes and tumor suppressor genes. Therefore, this study was conducted to determine the status of hotspot regions in DDR2 and KRAS genes for the first time, as well as in TP53 gene, in lung cancer patients within the Iranian population.

Experimental design

The mutations in exon 2 of KRAS, exon 18 of DDR2, and exons 5–6 of TP53 genes were screened in lung cancer samples, including non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) using PCR and sequencing techniques.

Results

Analysis of the KRAS gene showed only a G12C variation in one large cell carcinoma (LCC) patient, whereas variants were not found in adenocarcinoma (ADC) and squamous cell carcinoma (SCC) cases. The Q808H variation in the DDR2 gene was detected in one SCC sample, while no variant was seen in the ADC and LCC subtypes. Variations in the TP53 gene were seen in all NSCLC subtypes, including six ADC (13.63%), seven SCC (15.9%) and two LCC (4.54%). Forty-eight variants were found in the TP53 gene. Of these, 15 variants were found in coding regions V147A, V157F, Q167Q, D186G, H193R, T211T, F212L and P222P, 33 variants in intronic regions rs1625895 (HGVS: c.672+62A>G), rs766856111 (HGVS: c.672+6G>A) and two new variants (c.560-12A>G and c.672+86T>C).

Conclusions

In conclusion, KRAS, DDR2, and TP53 variants were detected in 2%, 2.17% and 79.54% of all cases, respectively. The frequency of DDR2 mutation is nearly close to other studies, while KRAS and TP53 mutation frequencies are lower and higher than other populations, respectively. Three new putative pathogenic variants, for the first time, have been detected in Iranian patients with lung cancer, including Q808H in DDR2, F212L, and D186G in coding regions of TP53. In addition, we observed five novel benign variants, including Q167Q, P222P and T211T in coding sequence, and c.560-12A>G and c.672+86T>C, in intronic region of TP53. Mutations of KRAS and DDR2 were found in LCC and SCC subtypes, respectively, whereas mutations of TP53 were seen in SCC and ADC subtypes with higher frequencies and LCC subtype with lower frequency. Therefore, Iranian lung cancer patients can benefit from mutational analysis before starting the conventional treatment. A better understanding of the biology of these genes and their mutations will be critical for developing future targeted therapies.