An Early-Onset Advanced Rectal Cancer Patient With Increased KRAS Gene Copy Number Showed A Primary Resistance to Cetuximab in Combination With Chemotherapy: A Case Report

Construction and validation of a novel algorithm based on oncosis-related lncRNAs comprising the immune landscape and prediction of colorectal cancer prognosis

Colorectal cancer (CRC) has high morbidity and mortality, particularly if diagnosed at an advanced stage. Although there have been several studies on CRC, few have investigated the relationship between oncosis and CRC. Thus, the purpose of the present study was to identify oncosis-related long noncoding RNAs (lncRNAs) and to establish a clinical prognostic model. Original data were acquired from The Cancer Genome Atlas database and PubMed. Differentially expressed oncosis-related lncRNAs (DEorlncRNAs) were identified and were subsequently formed into pairs. Next, a series of tests and analyses, including both univariate and multivariate analyses, as well as Lasso and Cox regression analyses, were performed to establish a receiver operating characteristic curve. A cut-off point was subsequently used to divide the samples into groups labelled as high- or low-risk. Thus, a model was established and evaluated in several dimensions. Six pairs of DEorlncRNAs associated with prognosis according to the algorithm were screened out and the CRC cases were divided into high- and low-risk groups. Significant differences between patients in the different risk groups were observed for several traits, including survival outcomes, clinical pathology characteristics, immune cell infiltration status and drug sensitivity. In addition, PCR and flow cytometry were performed to further verify the model. In summary, a new risk model algorithm based on six pairs of DEorlncRNAs in CRC, which does not require specific data regarding the level of gene expression, was established and validated. This algorithm may be used to predict patient prognosis, immune cell infiltration and drug sensitivity.

KRAS Gene Copy Number as a Negative Predictive Biomarker for the Treatment of Metastatic Rectal Cancer With Cetuximab: A Case Report

Background

Close to one third of colorectal cancer (CRC) patients are diagnosed with metastatic CRC (mCRC). Patients with wild-type RAS and BRAF usually receive anti-EGFR monoclonal antibody therapy containing cetuximab. Overall, 30–50% of mCRC patients are reported to harbor RAS mutations, and RAS mutation status should be assessed when considering EGFR inhibitor treatment according to mCRC biomarker guidelines. Of note, 0.67–2% of patients with CRC harbored a KRAS amplification. Here we reported a case of advanced rectal cancer with wild-type RAS and BRAF in a male patient who harbored a KRAS amplification during anti-EGFR treatment.

Case Presentation

A 46-year-old man was diagnosed with rectal adenocarcinoma with liver metastases (cT3NxM1a, stage IVA). After receiving first-line irinotecan- fluorouracil chemotherapy (FOLFIRI) plus cetuximab, second-line capecitabine- oxaliplatin chemotherapy (XELOX) plus bevacizumab, and third-line regorafenib, he rechallenged FOLFIRI and cetuximab for seven cycles, achieving a prolonged survival of at least 5 months. The KRAS copy number of circulating tumor DNA (ctDNA) was assessed during treatment. Notably, apart from serum carbohydrate antigen 199 (CA199) and carcinoembryonic antigen (CEA), the change of plasm Kirsten Rat Sarcoma Viral Oncogene Homolog (KRAS) copy number appeared to strongly correlate with treatment response.

Conclusion

Our findings suggest that the dynamic change of KRAS copy number on ctDNA during treatment might be a negative predictive biomarker. Additionally, RAS and BRAF wild-type mCRC patients who are resistant to first-line FOLFIRI plus cetuximab therapy may respond well to the FOLFIRI plus cetuximab “rechallenged” strategy.