Clinical Application of Targeted Deep Sequencing in Metastatic Colorectal Cancer Patients: Actionable Genomic Alteration in K-MASTER Project

Tumor mutational burden in colorectal cancer: Implications for treatment

Although immune checkpoint inhibitors have revolutionized the treatment of several advanced solid cancers, in colorectal cancer, the transformative benefit of these innovative medicines is currently limited to those with deficient mismatch repair or high microsatellite instability. Tumor mutational burden (TMB) has emerged as a potential predictor of immunotherapy benefit, but the lack of standardization in its assessment and reporting has hindered the introduction of this biomarker in routine clinical practice. Here, we compiled 45 colorectal cancer studies utilizing numerical thresholds for high-TMB. In this group of studies, TMB cut-offs ranged from 6.88 to 41 mut/Mb and were most often set at 10, 17, or 20 mut/Mb. Additionally, we observed divergent TMB definitions and inconsistent disclosure of specific methodological details, which collectively emphasize the substantial lack of harmonization within the field. Ongoing efforts to harmonize TMB assessment will be critical to validate TMB as a predictive marker of immunotherapy response.

Integrated clinical and genomic models using machine-learning methods to predict the efficacy of paclitaxel-based chemotherapy in patients with advanced gastric cancer

BACKGROUND

Paclitaxel is commonly used as a second-line therapy for advanced gastric cancer (AGC). The decision to proceed with second-line chemotherapy and select an appropriate regimen is critical for vulnerable patients with AGC progressing after first-line chemotherapy. However, no predictive biomarkers exist to identify patients with AGC who would benefit from paclitaxel-based chemotherapy.

METHODS

This study included 288 patients with AGC receiving second-line paclitaxel-based chemotherapy between 2017 and 2022 as part of the K-MASTER project, a nationwide government-funded precision medicine initiative. The data included clinical (age [young-onset vs. others], sex, histology [intestinal vs. diffuse type], prior trastuzumab use, duration of first-line chemotherapy), and genomic factors (pathogenic or likely pathogenic variants). Data were randomly divided into training and validation sets (0.8:0.2). Four machine learning (ML) methods, namely random forest (RF), logistic regression (LR), artificial neural network (ANN), and ANN with genetic embedding (ANN with GE), were used to develop the prediction model and validated in the validation sets.

RESULTS

The median patient age was 64 years (range 25-91), and 65.6% of those were male. A total of 288 patients were divided into the training (n = 230) and validation (n = 58) sets. No significant differences existed in baseline characteristics between the training and validation sets. In the training set, the areas under the ROC curves (AUROC) for predicting better progression-free survival (PFS) with paclitaxel-based chemotherapy were 0.499, 0.679, 0.618, and 0.732 in the RF, LR, ANN, and ANN with GE models, respectively. The ANN with the GE model that achieved the highest AUROC recorded accuracy, sensitivity, specificity, and F1-score performance of 0.458, 0.912, 0.724, and 0.579, respectively. In the validation set, the ANN with GE model predicted that paclitaxel-sensitive patients had significantly longer PFS (median PFS 7.59 vs. 2.07 months, P = 0.020) and overall survival (OS) (median OS 14.70 vs. 7.50 months, P = 0.008). The LR model predicted that paclitaxel-sensitive patients showed a trend for longer PFS (median PFS 6.48 vs. 2.33 months, P = 0.078) and OS (median OS 12.20 vs. 8.61 months, P = 0.099).

CONCLUSIONS

These ML models, integrated with clinical and genomic factors, offer the possibility to help identify patients with AGC who may benefit from paclitaxel chemotherapy.

Genomic analysis of plasma circulating tumor DNA in patients with heavily pretreated HER2 + metastatic breast cancer

We explored accumulated genomic alterations in patients with heavily treated HER2 + metastatic breast cancer enrolled in the KCSG BR18-14/KM10B trial. Targeted sequencing was performed with circulating tumor DNAs (ctDNAs) collected before the treatment of 92 patients. ctDNAs collected at the time of disease progression from seven patients who had a durable response for > 12 months were also analyzed. Sixty-five genes were identified as pathogenic alterations in 99 samples. The most frequently altered genes were TP53 (n = 48), PIKCA (n = 21) and ERBB3 (n = 19). TP53 and PIK3CA mutations were significantly related with shorter progression free survival (PFS), and patients with a higher ctDNA fraction showed a worse PFS. The frequency of homologous recombination deficiency (HRD)-related gene mutations was higher than that in matched tumor tissues, and these mutations tended to be associated with shorter PFS. New pathogenic variants were found at the end of treatment in all seven patients, including BRCA2, VHL, RAD50, RB1, BRIP1, ATM, FANCA, and PIK3CA mutations. In conclusion, TP53 and PIK3CA mutations, as well as a higher ctDNA fraction, were associated with worse PFS with trastuzumab and cytotoxic chemotherapy. The enrichment of HRD-related gene mutations and newly detected variants in ctDNA may be related to resistance to treatment.

Patient-Derived Organoids for In Vivo Validation of In Vitro Data

Patient-derived organoids are promising tumor models for functional validation of next-generation sequencing-based therapy recommendations. In times of rapidly advancing precision oncology approaches in everyday clinical processes, reliable and valid tumor models are required. Tumor organoids consist of tumor "stem" cells, differentiated (epithelial) tumor, and stroma cells. The cellular architecture and interactions closely mimic the original patient tumor. These organoids can be implanted into immunodeficient mice, generating patient-derived organoid-derived xenografts, thus enabling in vitro to in vivo transfer. Most importantly, the high clinical relevance of PDO models is maintained in this conversion. This protocol describes in detail the methods and techniques as well as the materials necessary to generate in vitro PDO and in vivo PDO-derived xenograft models. The elaborate process description starts with the processing of freshly obtained tumor tissue. The proceedings include tissue processing, organoid culturing, PDO implantation into immunodeficient mice, tumor explantation, and finally tumor preservation. All these proceedings are described in this timely chronological order. This protocol will enable researchers to generate PDO models from freshly received tumor tissue and generate PDO-derived xenografts. Models generated according to these methods are suitable for a very broad research spectrum.

Phase II study to investigate the efficacy of trastuzumab biosimilar (Herzuma®) plus treatment of physician's choice (TPC) in patients with heavily pretreated HER-2+ metastatic breast cancer (KCSG BR 18–14/KM10B)

We investigated the efficacy and safety of a trastuzumab biosimilar, Herzuma®, in combination with treatment of physician's choice (TPC) in patients with HER2+ metastatic breast cancer (MBC) who had failed at least two HER2 directed chemotherapies.

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Treatment of HER2-positive breast cancer is rapidly evolving with the development of new agents. However, treatment options are still limited after progression with proven anti-HER2 therapies.

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The combination of chemotherapy with a trastuzumab biosimilar, Herzuma®, was effective and safe in patients with heavily pre-treated HER2+ MBC.

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Duration of response to previous anti-HER2 therapy, PIK3CA and ERBB2 mutations were associated with clinical efficacies of trastuzumab biosimilar plus chemotherapy.

Genetic landscape of pancreatic adenocarcinoma patients: a pilot study from Pakistan

BACKGROUND

Pancreatic adenocarcinoma is one of the most aggressive malignancies with extremely low survival rate. Studies have shown that the exploration of key genes can provide a basis for targeted treatment of these patients. The genomic architecture of the Pakistani pancreatic adenocarcinoma patients remains unexplored. Keeping the scenario in place, the current study aims to analyse 88 cancer related genes in Pakistani pancreatic adenocarcinoma patients in order to elucidate candidate gene(s) for targeted molecular therapy.

METHODS AND RESULTS

A total 18 patients were included in the study initially and FFPE tumor samples were obtained. After confirmation of diagnosis and appropriate tumor content, DNA was extracted. Based on the quality and quantity of the extracted DNA, six pancreatic adenocarcinoma tumor samples were selected. Following to this, all the samples were subjected to targeted sequencing (Axen Cancer Panel 1). Variant detection was done and clinical significance of identified variants was assessed using ClinVar database. Targeted sequencing of tumor samples revealed a total of 29 alterations in the coding region of various genes. Among these five pathogenic variants were found in KRAS, BRCA1, TP53 and APC genes.

CONCLUSION

This is the first study that explores genes involved in pancreatic adenocarcinoma from the Pakistani population. Results obtained from the pilot study can guide us about the key genetic players in the Pakistani pancreatic adenocarcinoma population. This can lead to our better understanding of the molecular targeted therapies for these patients and designing future researches on larger sample size.

Recommendations for the Use of Next-Generation Sequencing and the Molecular Tumor Board for Patients with Advanced Cancer: A Report from KSMO and KCSG Precision Medicine Networking Group

Next-generation sequencing (NGS) is becoming essential in the fields of precision oncology. With implementation of NGS in daily clinic, the needs for continued education, facilitated interpretation of NGS results and optimal treatment delivery based on NGS results have been addressed. Molecular tumor board (MTB) is multidisciplinary approach to keep pace with the growing knowledge of complex molecular alterations in patients with advanced solid cancer. Although guidelines for NGS use and MTB have been developed in western countries, there is limitation for reflection of Korea’s public health environment and daily clinical practice. These recommendations provide a critical guidance from NGS panel testing to final treatment decision based on MTB discussion.

Implications of Intratumor Heterogeneity on Consensus Molecular Subtype (CMS) in Colorectal Cancer

The implications of intratumor heterogeneity on the four consensus molecular subtypes (CMS) of colorectal cancer (CRC) are not well known. Here, we use single-cell RNA sequencing (scRNASeq) to build an algorithm to assign CMS classification to individual cells, which we use to explore the distributions of CMSs in tumor and non-tumor cells. A dataset of colorectal tumors with bulk RNAseq (n = 3232) was used to identify CMS specific-marker gene sets. These gene sets were then applied to a discovery dataset of scRNASeq profiles (n = 10) to develop an algorithm for single-cell CMS (scCMS) assignment, which recapitulated the intrinsic biology of all four CMSs. The single-cell CMS assignment algorithm was used to explore the scRNASeq profiles of two prospective CRC tumors with mixed CMS via bulk sequencing. We find that every CRC tumor contains individual cells of each scCMS, as well as many individual cells that have enrichment for features of more than one scCMS (called mixed cells). scCMS4 and scCMS1 cells dominate stroma and immune cell clusters, respectively, but account for less than 3% epithelial cells. These data imply that CMS1 and CMS4 are driven by the transcriptomic contribution of immune and stromal cells, respectively, not tumor cells.

Evaluation of a Targeted Next-Generation Sequencing Panel for the Non-Invasive Detection of Variants in Circulating DNA of Colorectal Cancer

Molecular profiling of circulating cell-free DNA (cfDNA) has shown utility for the management of colorectal cancer (CRC). TruSight Tumor 170 (TST170) is a next-generation sequencing (NGS) panel that covers 170 cancer-related genes, including KRAS, which is a key driver gene in CRC. We evaluated the capacity of TST170 to detect gene variants in cfDNA from a retrospective cohort of 20 metastatic CRC patients with known KRAS variants in tumor tissue and in cfDNA previously analyzed by pyrosequencing and BEAMing, respectively. The cfDNA of most of the patients (95%) was successfully sequenced. We frequently detected variants with clinical significance in KRAS (79%, 15/19) and PIK3CA (26%, 5/19) genes. Variants with potential clinical significance were also identified in another 27 cancer genes, such as APC. The type of KRAS variant detected in cfDNA by TST170 showed high concordance with those detected in tumor tissue (77%), and very high concordance with cfDNA analyzed by BEAMing (94%). The variant allele fractions for KRAS obtained in cfDNA by TST170 and BEAMing correlated strongly. This proof-of-principle study indicates that targeted NGS analysis of cfDNA with TST170 could be useful for non-invasive detection of gene variants in metastatic CRC patients, providing an assay that could be easily implemented for detecting somatic alterations in the clinic.

Paired analysis of tumor mutation burden calculated by targeted deep sequencing panel and whole exome sequencing in non-small cell lung cancer

Owing to rapid advancements in NGS (next generation sequen-cing), genomic alteration is now considered an essential pre-dictive biomarkers that impact the treatment decision in many cases of cancer. Among the various predictive biomarkers, tumor mutation burden (TMB) was identified by NGS and was con-sidered to be useful in predicting a clinical response in cancer cases treated by immunotherapy. In this study, we directly com-pared the lab-developed-test (LDT) results by target sequencing panel, K-MASTER panel v3.0 and whole-exome sequencing (WES) to evaluate the concordance of TMB. As an initial step, the reference materials (n = 3) with known TMB status were used as an exploratory test. To validate and evaluate TMB, we used one hundred samples that were acquired from surgically resected tissues of non-small cell lung cancer (NSCLC) patients. The TMB of each sample was tested by using both LDT and WES methods, which extracted the DNA from samples at the same time. In addition, we evaluated the impact of capture re-gion, which might lead to different values of TMB; the evalu-ation of capture region was based on the size of NGS and target sequencing panels. In this pilot study, TMB was evalu-ated by LDT and WES by using duplicated reference samples; the results of TMB showed high concordance rate (R² = 0.887). This was also reflected in clinical samples (n = 100), which showed R² of 0.71. The difference between the coding sequence ratio (3.49%) and the ratio of mutations (4.8%) indicated that the LDT panel identified a relatively higher number of mutations. It was feasible to calculate TMB with LDT panel, which can be useful in clinical practice. Furthermore, a customized approach must be developed for calculating TMB, which differs according to cancer types and specific clinical settings.

The importance of precision medicine in modern molecular oncology

With the rapid development of modern medical technology, information data modeling has been gradually applied to clinical diagnosis and treatment. Precision medicine is an important approach that focuses on individual patients in terms of their own characteristics, genomic information, proteomics and even social environments. Genome-wide high-throughput technologies, including DNA-seq, RNA-seq, exosome-seq…, contribute enormous amounts of molecular data to aid in diagnosis and analysis. Here, we review the developmental history of different next-generation sequencing platforms, introduce their applications in different tumor diagnosis and therapy, and further discuss the remaining challenges in precision medicine.

Comparison of the Data of a Next-Generation Sequencing Panel from K-MASTER Project with that of Orthogonal Methods for Detecting Targetable Genetic Alterations

Purpose

K-MASTER project is a Korean national precision medicine platform that screened actionable mutations by analyzing next-generation sequencing (NGS) of solid tumor patients. We compared gene analyses between NGS panel from the K-MASTER project and orthogonal methods.

Materials and Methods

Colorectal, breast, non–small cell lung, and gastric cancer patients were included. We compared NGS results from K-MASTER projects with those of non-NGS orthogonal methods (KRAS, NRAS, and BRAF mutations in colorectal cancer [CRC]; epidermal growth factor receptor [EGFR], anaplastic lymphoma kinase [ALK] fusion, and reactive oxygen species 1 [ROS1] fusion in non–small cell lung cancer [NSCLC], and Erb-B2 receptor tyrosine kinase 2 (ERBB2) positivity in breast and gastric cancers).

Results

In the CRC cohort (n=225), the sensitivity and specificity of NGS were 87.4% and 79.3% (KRAS); 88.9% and 98.9% (NRAS); and 77.8% and 100.0% (BRAF), respectively. In the NSCLC cohort (n=109), the sensitivity and specificity of NGS for EGFR were 86.2% and 97.5%, respectively. The concordance rate for ALK fusion was 100%, but ROS1 fusion was positive in only one of three cases that were positive in orthogonal tests. In the breast cancer cohort (n=260), ERBB2 amplification was detected in 45 by NGS. Compared with orthogonal methods that integrated immunohistochemistry and in situ hybridization, sensitivity and specificity were 53.7% and 99.4%, respectively. In the gastric cancer cohort (n=64), ERBB2 amplification was detected in six by NGS. Compared with orthogonal methods, sensitivity and specificity were 62.5% and 98.2%, respectively.

Conclusion

The results of the K-MASTER NGS panel and orthogonal methods showed a different degree of agreement for each genetic alteration, but generally showed a high agreement rate.