Key differences between 13 KRAS mutation detection technologies and their relevance for clinical practice

Predicting response to neoadjuvant chemotherapy with liquid biopsies and multiparametric MRI in patients with breast cancer

Accurate prediction of response to neoadjuvant chemotherapy (NAC) can help tailor treatment to individual patients' needs. Little is known about the combination of liquid biopsies and computer extracted features from multiparametric magnetic resonance imaging (MRI) for the prediction of NAC response in breast cancer. Here, we report on a prospective study with the aim to explore the predictive potential of this combination in adjunct to standard clinical and pathological information before, during and after NAC. The study was performed in four Dutch hospitals. Patients without metastases treated with NAC underwent 3 T multiparametric MRI scans before, during and after NAC. Liquid biopsies were obtained before every chemotherapy cycle and before surgery. Prediction models were developed using penalized linear regression to forecast residual cancer burden after NAC and evaluated for pathologic complete response (pCR) using leave-one-out-cross-validation (LOOCV). Sixty-one patients were included. Twenty-three patients (38%) achieved pCR. Most prediction models yielded the highest estimated LOOCV area under the curve (AUC) at the post-treatment timepoint. A clinical-only model including tumor grade, nodal status and receptor subtype yielded an estimated LOOCV AUC for pCR of 0.76, which increased to 0.82 by incorporating post-treatment radiological MRI assessment (i.e., the "clinical-radiological" model). The estimated LOOCV AUC was 0.84 after incorporation of computer-extracted MRI features, and 0.85 when liquid biopsy information was added instead of the radiological MRI assessment. Adding liquid biopsy information to the clinical-radiological resulted in an estimated LOOCV AUC of 0.86. In conclusion, inclusion of liquid biopsy-derived markers in clinical-radiological prediction models may have potential to improve prediction of pCR after NAC in breast cancer.

Subtyping of advanced lung cancer based on PD-L1 expression, tumor histopathology and mutation burden (EGFR and KRAS): a study from North India

Immune checkpoint inhibitor (PD-L1) therapy of advanced non-small-cell lung cancer (NSCLC) has variable outcomes. Tumor subtypes based on PD-L1 expression, histopathology, mutation burden is required for patient stratification and formulation of treatment guidelines. Lung cancers (n=57) diagnosed at Pathology department, VPCI (2018-2021) were retrospectively analyzed. PD-L1(SP263) expressed by tumor cells [low (<1%), medium (1-49%), high (≥50%)] was correlated with histopathology, microenvironment, EGFR, KRAS expression. Patients were categorized into high and low risk based on their: i) gender: males (n=47, 30-89 years), females (n=10, 45-80 years); ii) smoking history: males 26/47 (45.61%), females 1/10 (10%); iii) tumor subtyping: squamous cell carcinoma 15/57 (26.32%), adenocarcinoma 6/57 (17.54%), NSCLC-undifferentiated 24/57 (42.10%), adenosquamous carcinoma 5/57 (8.77 %), carcinosarcoma 4/57 (7.02%), small cell carcinoma 1/57 (1.75%); iv) inflammatory tumor microenvironment/TILs 44/57 (77.1%); iv) PD-L1 positivity-31/57 (54.3%); v) concomitant EGFR/KRAS positivity. PD-L1positive cases showed squamous/undifferentiated histopathology, concomitant EGFR+ (9/20, 45%) and KRAS+ (8/15, 53.3%), smoking+ (21/31,67.74%).PD-L1 negative cases (26/57, 45.6%), were EGFR+ (2/14, 14.28%) and KRAS+ (6/19, 31.5%). The high-risk lung cancer subtypes show squamous/undifferentiated histopathology, inflammatory microenvironment, male preponderance, smoking history, higher concomitant PD-L1, KRAS and EGFR positivity. Lung cancer subtyping can predict clinical response/resistance of patients prior to initiation of PD-L1 inhibitor therapies and can be used to guide therapy.

Expert opinion on NSCLC small specimen biomarker testing - Part 1: Tissue collection and management

Biomarker testing is crucial for treatment selection in advanced non-small cell lung cancer (NSCLC). However, the quantity of available tissue often presents a key constraint for patients with advanced disease, where minimally invasive tissue biopsy typically returns small samples. In Part 1 of this two-part series, we summarise evidence-based recommendations relating to small sample processing for patients with NSCLC. Generally, tissue biopsy techniques that deliver the greatest quantity and quality of tissue with the least risk to the patient should be selected. Rapid on-site evaluation can help to ensure sufficient sample quality and quantity. Sample processing should be managed according to biomarker testing requirements, because tissue fixation methodology influences downstream nucleic acid, protein and morphological analyses. Accordingly, 10% neutral buffered formalin is recommended as an appropriate fixative, and the duration of fixation is recommended not to exceed 24–48 h. Tissue sparing techniques, including the ‘one biopsy per block’ approach and small sample cutting protocols, can help preserve tissue. Cytological material (formalin-fixed paraffin-embedded [FFPE] cytology blocks and non-FFPE samples such as smears and touch preparations) can be an excellent source of nucleic acid, providing either primary or supplementary patient material to complete morphological and molecular diagnoses. Considerations on biomarker testing, reporting and quality assessment are discussed in Part 2.

Concomitant KRAS mutations attenuate sensitivity of non-small cell lung cancer cells to KRAS G12C inhibition

The development of covalent inhibitors against KRAS G12C represents a major milestone in treatment of RAS-driven cancers, especially in non-small cell lung cancer (NSCLC), where KRAS G12C is one of the most common oncogenic driver. Here we investigated if additional KRAS mutations co-occur with KRAS G12C (c.34G>T) in NSCLC tumours and if such mutation co-occurrence affects cellular response to G12C-specific inhibitors. Analysis of a large cohort of NSCLC patients whose tumours harboured KRAS mutations revealed co-occurring KRAS mutations in up to 8% of tumours with the KRAS c.34G>T mutation. KRAS c.35G>T was the most frequently co-occurring mutation, and could occur on the same allele (in cis) translating to a single mutant KRAS G12F protein, or on the other allele (in trans), translating to separate G12C and G12V mutant proteins. Introducing KRAS c.35G>T in trans in the KRAS G12C lung cancer model NCI-H358, as well as the co-occurrence in cis in the KRAS G12F lung cancer model NCI-H2291 led to cellular resistance to the G12C-specific inhibitor AZ’8037 due to continuing active MAPK and PI3K cascades in the presence of the inhibitor. Overall, our study provides a comprehensive assessment of co-occurring KRAS mutations in NSCLC and in vitro evidence of the negative impact of co-occurring KRAS mutations on cellular response to G12C inhibitors, highlighting the need for a comprehensive KRAS tumour genotyping for optimal patient selection for treatment with a KRAS G12C inhibitor.

Rapid clinical mutational testing of KRAS, BRAF and EGFR: a prospective comparative analysis of the Idylla technique with high-throughput next-generation sequencing

AIMS

Precision medicine therapy is remodelling the diagnostic landscape of cancer. The success of these new therapies is often based on the presence or absence of a specific mutation in a tumour. The Idylla platform is designed to determine the mutational status of a tumour as quickly and accurately as possible, as a rapid, accurate diagnosis is of the utmost importance for the treatment of patients. This is the first complete prospective study to investigate the robustness of the Idylla platform for EGFR, KRAS and BRAF mutations in non-small cell lung cancer, metastatic colorectal cancer and metastatic melanoma, respectively.

METHODS

We compared prospectively the Idylla platform with the results we obtained from parallel high-throughput next-generation sequencing, which is the current gold standard for mutational testing. Furthermore, we evaluated the benefits and disadvantages of the Idylla platform in clinical practice. Additionally, we reviewed all the published Idylla performance articles.

RESULTS

There was an overall agreement of 100%, 94% and 94% between the next-generation panel and the Idylla BRAF, KRAS and EGFR mutation test. Two interesting discordant findings among 48 cases were observed and will be discussed together with the advantages and shortcoming of both techniques.

CONCLUSION

Our observations demonstrate that the Idylla cartridge for the EGFR, KRAS and BRAF mutations is highly accurate, rapid and has a limited hands-on time compared with next-generation sequencing.

Droplet digital PCR revealed high concordance between primary tumors and lymph node metastases in multiplex screening of KRAS mutations in colorectal cancer

The proto-oncogene KRAS belongs among the most frequently mutated genes in all types of cancer and is also very important oncogene related to colorectal tumors. The detection of mutations in this gene in primary tumor is a predictive biomarker for the anti-EGFR therapy in metastatic CRC (mCRC); however, the patients with wild-type KRAS can also show resistance to the personalized medicine. The droplet-based digital PCR technology has improved the analytical sensitivity of the mutations detection, which led us to the idea about the optimization of this approach for KRAS testing. In this study, we report the application of ddPCR technology in order to analyze the presence of KRAS mutations in primary tumor and matched metastasis in lymph nodes (LNs) from patients with mCRC and address the question, whether the improvement in the detection method can lower the discrepancies of KRAS mutations detection between the primary tumor and regional LNs. Genomic DNA with wtKRAS and commercial DNA with mtKRAS (G12D) were used to set up the ddPCR reaction. Formalin-fixed paraffin-embedded tissues from primary tumor and positive lymph node from 31 patients with mCRC were analyzed using ddPCR and Sanger sequencing. KRAS status of primary tumors was known; however, the mutation status of lymph nodes was not detected previously. From 31 samples of primary tumors, our results corresponded to results from IVD kit in 30 cases. For one patient, ddPCR detected KRAS mutation in comparison with negative result of the IVD kit. In the samples of metastatic infiltrated LNs, ddPCR detected 16 samples as a WT KRAS and 15 lymph nodes showed positivity for KRAS mutation, whereby Sanger sequencing found KRAS mutations in 8 cases only. We also found two cases where genetic conditions of KRAS gene differed between primary tumor and infiltrated lymph node, both "low-grade" adenocarcinoma. Our study approved that ddPCR method is adequate technique with high sensitivity and in the future may be used as a diagnostic tool for evaluation of KRAS mutations, especially in infiltrated LNs of patients with mCRC.

Response: Concerns with conclusions in the article by Sherwood et al ‘Key differences between 13 KRAS mutation detection technologies and their relevance for clinical practice’

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Concerns with conclusions in the article by Sherwood et al ‘Key differences between 13 KRAS mutation detection technologies and their relevance for clinical practice’

Click here and here to see the linked papers