Retrospective analysis of KRAS status in metastatic colorectal cancer patients: a single-center feasibility study

Synergistic Approach of Antibody-Photosensitizer Conjugate Independent of KRAS-Mutation and Its Downstream Blockade Pathway in Colorectal Cancer

Here, a novel approach is presented to improve the efficacy of antibody-drug conjugates (ADC) by integrating antibody-mediated immunotherapy and photodynamic therapy (PDT) in a combination therapy system utilizing an antibody-photosensitizer conjugate (APC) platform based on a poloxamer polymer linker. To specifically target Kirsten rat sarcoma 2 viral oncogene homolog (KRAS)-mutated cancer cells, an antibody antiepidermal growth factor receptor (EGFR), cetuximab, with a poloxamer linker coupled with the photosensitizer chlorin e6 through click chemistry (cetuximab-maleimide-poly(ethylene oxide)-poly(propylene oxide)-poly(ethylene oxide)-chlorine e6 conjugate, CMPXC) is synthesized. CMPXC is cytotoxic upon laser treatment, achieving a 90% cell death by suppressing KRAS downstream signaling pathways associated with ERK and AKT proteins, confirmed using RNA sequencing analysis. In KRAS-mutated colorectal cancer mouse models, CMPXC significantly enhances antitumor efficacy compared with cetuximab treatment alone, resulting in an 86% reduction in tumor growth. Furthermore, CMPXC treatment leads to a 2.24- and 1.75-fold increase in dendritic and priming cytotoxic T cells, respectively, highlighting the immune-activating potential of this approach. The findings suggest that the APC platform addresses the challenges associated with ADC development and EGFR-targeted therapy, including the synergistic advantages of antibody-mediated immunotherapy and PDT.

High Frequency of KRAS Codon 146 and FBXW7 Mutations in Thai Patients with Stage II-III Colon Cancer

Background: KRAS, NRAS, and BRAF gene mutations are the most clinically relevant and frequently reported in colorectal cancer (CRC). Although data on these genes are frequently reported in several counties, data specific to these genes among Thai population are scarce. The aim of this study was to investigate and identify molecular alterations associated with colon cancer in Thai population, and to determine the impact of these genetic aberrations on clinical outcome. Methods: DNA from 108 archived formalin-fixed, paraffin-embedded (FFPE) tissue samples that histologically confirmed adenocarcinoma of stage II-III colon cancer between 2010 and 2012 at Siriraj Hospital (Bangkok, Thailand) were extracted. Gene mutational analysis was performed by next-generation sequencing (NGS) using an Oncomine Solid Tumor DNA kit (Thermo Fisher Scientific, Inc., Waltham, MA, USA). Results: A total of 22 somatic gene mutations were detected. The mutation frequency observed in KRAS, NRAS, BRAF, PIK3CA, and FBXW7 mutations was 47.2%, 1.9%, 1.9%, 12%, and 14.8%, respectively. KRAS mutation codon 12, 13, 59, 61, 117, and 146 mutations were identified in 29.6%, 8.3%, 1.8%, 0.9%, 0.0%, and 8.3%, respectively. KRAS Exon 4 had better DFS compared with Exon 2 and 3. Conclusions: This study is the first to comprehensively report hotspot mutations using NGS in Thai colon cancer patients. The most commonly identified gene mutation frequencies among Thai patients (KRAS, NRAS, BRAF, TP53, and PIK3CA) were similar to the gene mutation frequencies reported in Western population, except for subgroup of KRAS codon 146 and FBXW7 mutations that had a slightly higher frequency.

Challenges of guarantee-time bias

The potential for guarantee-time bias (GTB), also known as immortal time bias, exists whenever an analysis that is timed from enrollment or random assignment, such as disease-free or overall survival, is compared across groups defined by a classifying event occurring sometime during follow-up. The types of events associated with GTB are varied and may include the occurrence of objective disease response, onset of toxicity, or seroconversion. However, comparative analyses using these types of events as predictors are different from analyses using baseline characteristics that are specified completely before the occurrence of any outcome event. Recognizing the potential for GTB is not always straightforward, and it can be challenging to know when GTB is influencing the results of an analysis. This article defines GTB, provides examples of GTB from several published articles, and discusses three analytic techniques that can be used to remove the bias: conditional landmark analysis, extended Cox model, and inverse probability weighting. The strengths and limitations of each technique are presented. As an example, we explore the effect of bisphosphonate use on disease-free survival (DFS) using data from the BIG (Breast International Group) 1-98 randomized clinical trial. An analysis using a naive approach showed substantial benefit for patients who received bisphosphonate therapy. In contrast, analyses using the three methods known to remove GTB showed no statistical evidence of a reduction in risk of a DFS event with bisphosphonate therapy.