KRAS mutation testing in clinical practice

Exosomal microRNAs in regulation of tumor cells resistance to apoptosis

Exosomes are a type of extracellular vesicle that contains bioactive molecules that can be secreted by most cells. Nevertheless, the content of these cells differs depending on the cell from which they originate. The exosome plays a crucial role in modulating intercellular communication by conveying molecular messages to neighboring or distant cells. Cancer-derived exosomes can transfer several types of molecules into the tumor microenvironment, including high levels of microRNA (miRNA). These miRNAs significantly affect cell proliferation, angiogenesis, apoptosis resistance, metastasis, and immune evasion. Increasing evidence indicates that exosomal miRNAs (exomiRs) are crucial to regulating cancer resistance to apoptosis. In cancer cells, exomiRs orchestrate communication channels between them and their surrounding microenvironment, modulating gene expression and controlling apoptosis signaling pathways. This review presents an outline of present-day knowledge of the mechanisms that affect target cells and drive cancer resistance to apoptosis. Also, our study looks at the regulatory role of exomiRs in mediating intercellular communication between tumor cells and surrounding microenvironmental cells, specifically stromal and immune cells, to evade therapy-induced apoptosis.

Four drug metabolism-related subgroups of pancreatic adenocarcinoma in prognosis, immune infiltration, and gene mutation

We aimed to screen the drug metabolism-related subgroups of pancreatic adenocarcinoma (PAAD) and to study the prognosis, clinical features, immune infiltration, and gene mutation differences of different subtypes in PAAD patients. All 181 cases of PAAD samples and clinical characteristics data were downloaded from The Cancer Genome Atlas (TCGA). After matching the drug metabolism-related genes downloaded from PMID 33202946 with the TCGA dataset, the drug metabolism-related genes were initially obtained. Besides, univariate Cox regression analysis was used to screen the drug metabolism genes related to the prognosis of PAAD. Moreover, the construction of the protein–protein interaction (PPI) network and gene ontology were performed. The four subgroups of PAAD obtained from unsupervised clustering analysis were systematically analyzed, including prognostic, GSVA, immune infiltration, and gene mutation analysis. A total of 83 drug metabolism genes related to the prognosis of PAAD were obtained and enriched in 16 pathways. The PPI network was composed of 248 relationship pairs. Four subgroups that can identify different subtypes of PPAD were obtained, and there were significant differences in survival and clinical characteristics, mutation types, and immune infiltration abundance between subgroups. A total of 17 different pathways among the four subgroups involved in cell cycle, response to stimulants such as drugs, and transmembrane transport. In this study, the four subgroups related to the drug metabolism of PAAD were comprehensively analyzed, and the important role of drug metabolism-related genes in the immune infiltration and prognosis of PAAD were emphasized.

Lipidomic profiling of human serum enables detection of pancreatic cancer

Pancreatic cancer has the worst prognosis among all cancers. Cancer screening of body fluids may improve the survival time prognosis of patients, who are often diagnosed too late at an incurable stage. Several studies report the dysregulation of lipid metabolism in tumor cells, suggesting that changes in the blood lipidome may accompany tumor growth. Here we show that the comprehensive mass spectrometric determination of a wide range of serum lipids reveals statistically significant differences between pancreatic cancer patients and healthy controls, as visualized by multivariate data analysis. Three phases of biomarker discovery research (discovery, qualification, and verification) are applied for 830 samples in total, which shows the dysregulation of some very long chain sphingomyelins, ceramides, and (lyso)phosphatidylcholines. The sensitivity and specificity to diagnose pancreatic cancer are over 90%, which outperforms CA 19-9, especially at an early stage, and is comparable to established diagnostic imaging methods. Furthermore, selected lipid species indicate a potential as prognostic biomarkers.

Targeting Cancer with CRISPR/Cas9-Based Therapy

Cancer is a devastating condition characterised by the uncontrolled division of cells with many forms remaining resistant to current treatment. A hallmark of cancer is the gradual accumulation of somatic mutations which drive tumorigenesis in cancerous cells, creating a mutation landscape distinctive to a cancer type, an individual patient or even a single tumour lesion. Gene editing with CRISPR/Cas9-based tools now enables the precise and permanent targeting of mutations and offers an opportunity to harness this technology to target oncogenic mutations. However, the development of safe and effective gene editing therapies for cancer relies on careful design to spare normal cells and avoid introducing other mutations. This article aims to describe recent advancements in cancer-selective treatments based on the CRISPR/Cas9 system, especially focusing on strategies for targeted delivery of the CRISPR/Cas9 machinery to affected cells, controlling Cas9 expression in tissues of interest and disrupting cancer-specific genes to result in selective death of malignant cells.

Mass spectrometric detection of KRAS protein mutations using molecular imprinting

Cancer is a disease of cellular evolution where single base changes in the genetic code can have significant impact on the translation of proteins and their activity. Thus, in cancer research there is significant interest in methods that can determine mutations and identify the significant binding sites (epitopes) of antibodies to proteins in order to develop novel therapies. Nano molecularly imprinted polymers (nanoMIPs) provide an alternative to antibodies as reagents capable of specifically capturing target molecules depending on their structure. In this study, we used nanoMIPs to capture KRAS, a critical oncogene, to identify mutations which when present are indicative of oncological progress. Herein, coupling nanoMIPs (capture) and liquid chromatography-mass spectrometry (detection), LC-MS has allowed us to investigate mutational assignment and epitope discovery. Specifically, we have shown epitope discovery by generating nanoMIPs to a recombinant KRAS protein and identifying three regions of the protein which have been previously assigned as epitopes using much more time-consuming protocols. The mutation status of the released tryptic peptide was identified by LC-MS following capture of the conserved region of KRAS using nanoMIPS, which were tryptically digested, thus releasing the sequence of a non-conserved (mutated) region. This approach was tested in cell lines where we showed the effective genotyping of a KRAS cell line and in the plasma of cancer patients, thus demonstrating its ability to diagnose precisely the mutational status of a patient. This work provides a clear line-of-sight for the use of nanoMIPs to its translation from research into diagnostic and clinical utility.

Detection of KRAS mutations in plasma cell-free DNA of colorectal cancer patients and comparison with cancer panel data for tissue samples of the same cancers

Robust identification of genetic alterations is important for the diagnosis and subsequent treatment of tumors. Screening for genetic alterations using tumor tissue samples may lead to biased interpretations because of the heterogeneous nature of the tumor mass. Liquid biopsy has been suggested as an attractive tool for the non-invasive follow-up of cancer treatment outcomes. In this study, we aimed to verify whether the mutations identified in primary tumor tissue samples could be consistently detected in plasma cell–free DNA (cfDNA) by digital polymerase chain reaction (dPCR). We first examined the genetic alteration profiles of three colorectal cancer (CRC) tissue samples by targeted next-generation sequencing (NGS) and identified 11 non-silent amino acid changes across six cancer-related genes (APC, KRAS, TP53, TERT, ARIDIA, and BRCA1). All three samples had KRAS mutations (G12V, G12C, and G13D), which were well-known driver events. Therefore, we examined the KRAS mutations by dPCR. When we examined the three KRAS mutations by dPCR using tumor tissue samples, all of them were consistently detected and the variant allele frequencies (VAFs) of the mutations were almost identical between targeted NGS and dPCR. When we examined the KRAS mutations using the plasma cfDNA of the three CRC patients by dPCR, all three mutations were consistently identified. However, the VAFs were lower (range, 0.166% to 2.638%) than those obtained using the CRC tissue samples. In conclusion, we confirmed that the KRAS mutations identified from CRC tumor tissue samples were consistently detected in the plasma cfDNA of the three CRC patients by dPCR.

Exosomal miRNA: Small Molecules, Big Impact in Colorectal Cancer

Colorectal cancer (CRC) is one of the major causes of cancer-related deaths worldwide. Tumor microenvironment (TME) contains many cell types including stromal cells, immune cells, and endothelial cells. The TME modulation explains the heterogeneity of response to therapy observed in patients. In this context, exosomes are emerging as major contributors in cancer biology. Indeed, exosomes are implicated in tumor proliferation, angiogenesis, invasion, and premetastatic niche formation. They contain bioactive molecules such as proteins, lipids, and RNAs. More recently, many studies on exosomes have focused on miRNAs, small noncoding RNA molecules able to influence protein expression. In this review, we describe miRNAs transported by exosomes in the context of CRC and discuss their influence on TME and their potential as circulating biomarkers. This overview underlines emerging roles for exosomal miRNAs in cancer research for the near future.

KRAS mutation of extraovarian implants of serous borderline tumor: prognostic indicator for adverse clinical outcome

In contrast to non-invasive extraovarian implants, invasive implants of ovarian serous borderline tumor/atypical proliferative serous tumor are associated with adverse outcome and have been reclassified as low-grade serous carcinoma. Mutations of KRAS and/or BRAF have been reported in up to 50% of serous borderline tumor/atypical proliferative serous tumor. We investigated KRAS and BRAF mutation frequencies in the two types of implants of serous borderline tumor/atypical proliferative serous tumor in correlation with clinical outcome. Forty-two implants of serous borderline tumor from 39 patients were included (invasive implants/low-grade serous carcinoma, n=20; non-invasive implants, n=22). KRAS mutation was found in 12 of 20 invasive implants (60%) and 3 of 22 non-invasive implants (14%). BRAF V600E mutation was found in 1 of 22 non-invasive implants (5%) and none in invasive implants (0%). Invasive implants were more frequently associated with higher stage disease. Nine of 14 patients (64%) with KRAS mutation were found to have stage IIIC disease, while 5 of 24 patients (20%) without the mutation had stage IIIC disease. Patients with invasive implants had higher recurrence rate compared to those with non-invasive implants (60 vs 14 %, P=0.0003, log-rank test) and worse disease-specific survival (P=0.0008, log-rank test). Regardless of the histological subtypes, patients with KRAS mutation positive implants had significantly higher recurrence rate than those without the mutation (71 vs 21%, P=0.0021, log-rank test) and an unfavorable disease-specific survival (P=0.0104, log-rank test). In conclusion, compared to those with non-invasive implants, patients with invasive implants present with higher stage of the disease, higher recurrence rate and worse survival. KRAS mutation, but not BRAF V600E mutation, is significantly associated with invasive implants of serous borderline tumor. Regardless of the histological subtypes of the implants, KRAS mutation is a significant prognostic indicator for high risk of tumor recurrence and worse disease-specific survival.

Digital PCR Improves Mutation Analysis in Pancreas Fine Needle Aspiration Biopsy Specimens

Applications of precision oncology strategies rely on accurate tumor genotyping from clinically available specimens. Fine needle aspirations (FNA) are frequently obtained in cancer management and often represent the only source of tumor tissues for patients with metastatic or locally advanced diseases. However, FNAs obtained from pancreas ductal adenocarcinoma (PDAC) are often limited in cellularity and/or tumor cell purity, precluding accurate tumor genotyping in many cases. Digital PCR (dPCR) is a technology with exceptional sensitivity and low DNA template requirement, characteristics that are necessary for analyzing PDAC FNA samples. In the current study, we sought to evaluate dPCR as a mutation analysis tool for pancreas FNA specimens. To this end, we analyzed alterations in the KRAS gene in pancreas FNAs using dPCR. The sensitivity of dPCR mutation analysis was first determined using serial dilution cell spiking studies. Single-cell laser-microdissection (LMD) was then utilized to identify the minimal number of tumor cells needed for mutation detection. Lastly, dPCR mutation analysis was performed on 44 pancreas FNAs (34 formalin-fixed paraffin-embedded (FFPE) and 10 fresh (non-fixed)), including samples highly limited in cellularity (100 cells) and tumor cell purity (1%). We found dPCR to detect mutations with allele frequencies as low as 0.17%. Additionally, a single tumor cell could be detected within an abundance of normal cells. Using clinical FNA samples, dPCR mutation analysis was successful in all preoperative FNA biopsies tested, and its accuracy was confirmed via comparison with resected tumor specimens. Moreover, dPCR revealed additional KRAS mutations representing minor subclones within a tumor that were not detected by the current clinical gold standard method of Sanger sequencing. In conclusion, dPCR performs sensitive and accurate mutation analysis in pancreas FNAs, detecting not only the dominant mutation subtype, but also the additional rare mutation subtypes representing tumor heterogeneity.

Predictive and prognostic cancer biomarkers revisited

While both prognostic and predictive cancer biomarkers predict clinical outcome, the term 'predictive biomarker' is reserved for the association of a specific therapy with a specific clinical outcome. The advent of genomic signatures and next generation sequencing as candidate predictive biomarkers has led to lengthy and expensive processes for biomarker qualification. The urgency to bring novel predictive cancer biomarkers to practice faster and cheaper requires strategies to lower the bar to biomarker implementation. Three strategies are suggested: identify biomarkers closely coupled to biologic mechanism associated with the clinical endpoint and scalable from cells to humans; identify biomarkers that can be reliably detected and quantified; and assess biomarkers by capacity to reduce toxicity as well as to increase therapy efficacy. Biomarker selection directly and closely related to production of end points by biologic mechanism demonstrated by a ladder of evidence should require less burden of proof clinically than biomarkers that are merely associative.