Neoadjuvant Chemotherapy Response in Triple-Negative Apocrine Carcinoma: Comparing Apocrine Morphology, Androgen Receptor, and Immune Phenotypes.

CONTEXT.­: Apocrine differentiation and androgen receptor (AR) positivity represent a specific subset of triple-negative breast cancer (TNBC) and are often considered potential prognostic or predictive factors. OBJECTIVE.­: To evaluate the response of TNBC to neoadjuvant chemotherapy (NAC) and to assess the impact of apocrine morphology, AR status, Ki-67 labeling index (Ki-67LI), and tumor-infiltrating lymphocytes (TILs). DESIGN.­: A total of 232 TNBC patients who underwent NAC followed by surgical resection in a single institute were analyzed. The study evaluated apocrine morphology and AR and Ki-67LI expression via immunohistochemistry from pre-NAC biopsy samples. Additionally, pre-NAC intratumoral TILs and stromal TILs (sTILs) were quantified from biopsies using a deep learning model. The response to NAC after surgery was assessed based on residual cancer burden. RESULTS.­: Both apocrine morphology and high AR expression correlated with lower Ki-67LI (P < .001 for both). Apocrine morphology was associated with lower postoperative pathologic complete response (pCR) rates after NAC (P = .02), but the difference in TILs between TNBC cases with and without apocrine morphology was not statistically significant (P = .09 for sTILs). In contrast, AR expression did not significantly affect pCR (P = .13). Pre-NAC TILs strongly correlated with postoperative pCR in TNBCs without apocrine morphology (P < .001 for sTILs), whereas TNBC with apocrine morphology demonstrated an indeterminate trend (P = .82 for sTILs). CONCLUSIONS.­: Although TIL counts did not vary significantly based on apocrine morphology, apocrine morphology itself was a more reliable predictor of NAC response than AR expression. Consequently, although apocrine morphology is a rare subtype of TNBC, its identification is clinically important.

A Phase II Open-Label Randomized Clinical Trial of Preoperative Durvalumab or Durvalumab plus Tremelimumab in Resectable Head and Neck Squamous Cell Carcinoma.

PURPOSE: Clinical implications of neoadjuvant immunotherapy in patients with locally advanced but resectable head and neck squamous cell carcinoma (HNSCC) remain largely unexplored. PATIENTS AND METHODS: Patients with resectable HNSCC were randomized to receive a single dose of preoperative durvalumab (D) with or without tremelimumab (T) before resection, followed by postoperative (chemo)radiotherapy based on multidisciplinary discretion and 1-year D treatment. Artificial intelligence (AI)-powered spatial distribution analysis of tumor-infiltrating lymphocytes and high-dimensional profiling of circulating immune cells tracked dynamic intratumoral and systemic immune responses. RESULTS: Of the 48 patients enrolled (D, 24 patients; D+T, 24 patients), 45 underwent surgical resection per protocol (D, 21 patients; D+T, 24 patients). D±T had a favorable safety profile and did not delay surgery. Distant recurrence-free survival (DRFS) was significantly better in patients treated with D+T than in those treated with D monotherapy. AI-powered whole-slide image analysis demonstrated that D+T significantly reshaped the tumor microenvironment toward immune-inflamed phenotypes, in contrast with the D monotherapy or cytotoxic chemotherapy. High-dimensional profiling of circulating immune cells revealed a significant expansion of T-cell subsets characterized by proliferation and activation in response to D+T therapy, which was rare following D monotherapy. Importantly, expansion of specific clusters in CD8+ T cells and non-regulatory CD4+ T cells with activation and exhaustion programs was associated with prolonged DRFS in patients treated with D+T. CONCLUSIONS: Preoperative D±T is feasible and may benefit patients with resectable HNSCC. Distinct changes in the tumor microenvironment and circulating immune cells were induced by each treatment regimen, warranting further investigation.

Inflamed immune phenotype predicts favorable clinical outcomes of immune checkpoint inhibitor therapy across multiple cancer types.

BACKGROUND: The inflamed immune phenotype (IIP), defined by enrichment of tumor-infiltrating lymphocytes (TILs) within intratumoral areas, is a promising tumor-agnostic biomarker of response to immune checkpoint inhibitor (ICI) therapy. However, it is challenging to define the IIP in an objective and reproducible manner during manual histopathologic examination. Here, we investigate artificial intelligence (AI)-based immune phenotypes capable of predicting ICI clinical outcomes in multiple solid tumor types. METHODS: Lunit SCOPE IO is a deep learning model which determines the immune phenotype of the tumor microenvironment based on TIL analysis. We evaluated the correlation between the IIP and ICI treatment outcomes in terms of objective response rates (ORR), progression-free survival (PFS), and overall survival (OS) in a cohort of 1,806 ICI-treated patients representing over 27 solid tumor types retrospectively collected from multiple institutions. RESULTS: We observed an overall IIP prevalence of 35.2% and significantly more favorable ORRs (26.3% vs 15.8%), PFS (median 5.3 vs 3.1 months, HR 0.68, 95% CI 0.61 to 0.76), and OS (median 25.3 vs 13.6 months, HR 0.66, 95% CI 0.57 to 0.75) after ICI therapy in IIP compared with non-IIP patients, respectively (p<0.001 for all comparisons). On subgroup analysis, the IIP was generally prognostic of favorable PFS across major patient subgroups, with the exception of the microsatellite unstable/mismatch repair deficient subgroup. CONCLUSION: The AI-based IIP may represent a practical, affordable, clinically actionable, and tumor-agnostic biomarker prognostic of ICI therapy response across diverse tumor types.

Discontinuation risk from adverse events: immunotherapy alone vs. combined with chemotherapy: a systematic review and network meta-analysis.

BACKGROUND: While immunotherapy combined with chemotherapy (Chemo-IO) is generally recognized for providing superior outcomes compared to monotherapy (mono-IO), it is associated with a higher incidence of treatment-related adverse events (TRAEs), which may lead to treatment discontinuation. In this study, we compared the rates of treatment discontinuation between mono-IO and Chemo-IO as first-line treatments for various solid tumors. METHODS: We systematically reviewed clinical trials from databases (PubMed, Embase, Cochrane Library, and an additional source) published from January 1, 2018, to July 10, 2023. We included phase III randomized controlled trials (RCTs) that utilized immunotherapy agents in at least one arm as first-line treatments for a variety of solid tumors. Data extraction followed the Preferred Reporting Items for Systematic Reviews (PRISMA) extension statement for network meta-analysis. A random effects model was used for the network meta-analysis, with the risk of bias assessed using the Cochrane risk-of-bias tool II. The primary outcomes encompassed treatment discontinuation rates due to TRAEs among patients who underwent immunotherapy, either alone or combined with chemotherapy, for various solid tumors. Pooled relative risks (RRs) with 95% confidence intervals (CIs) were calculated to compare between treatment groups. RESULTS: From 29 RCTs, a total of 21,677 patients and 5 types of treatment were analyzed. Compared to mono-IO, Chemo-IO showed a significantly higher rate of discontinuation due to TRAEs (RR 2.68, 95% CI 1.98-3.63). Subgroup analysis for non-small cell lung cancer (NSCLC) patients also exhibited a greater risk of discontinuation due to TRAEs with Chemo-IO compared to mono-IO (RR 2.93, 95% CI 1.67-5.14). Additional analyses evaluating discontinuation rates due to either treatment emergent adverse events (TEAEs) or AEs regardless of causality (any AEs) consistently revealed an elevated risk associated with Chemo-IO. CONCLUSIONS: Chemo-IO was associated with an elevated risk of treatment discontinuation not only due to TRAEs but also any AEs or TEAEs. Given that the treatment duration can impact clinical outcomes, a subset of patients might benefit more from mono-IO than combination therapy. Further research is imperative to identify and characterize this subset.

Analytical and Clinical Validation of a Highly Sensitive NGS-Based ctDNA Assay with Real-World Concordance in Non-Small Cell Lung Cancer.

PURPOSE: There have been needs to improve the sensitivity of liquid biopsy. This report aims to report the analytical and clinical validation of a next-generation sequencing (NGS)-based circulating tumor DNA (ctDNA) assay. MATERIALS AND METHODS: Analytical validation was conducted in vitro by evaluating the limit of detection (LOD), precision, and specificity for various genomic aberrations. The real-world performance in non-small cell lung cancer (NSCLC) was assessed by comparing the results of AlphaLiquid100 to the tissue-based results. RESULTS: The LODs with 30 ng input DNA were 0.11%, 0.11%, 0.06%, 0.21%, and 2.13 copies for detecting single nucleotide variants, insertions, deletions, fusions, and copy number alterations (CNA), respectively. Quantitatively, single nucleotide variants/insertions and deletions, fusions, and CNAs showed a good correlation (R2=0.91, 0.40, and 0.65; y=0.95, 1.06, and 1.19) to the manufacturer's values, and per-base specificities for all types of variants were near 100%. In real-world NSCLC (n=122), key actionable mutations in NSCLC were detected in 60.7% (74/122) with the ctDNA assay. Comparative analysis against the NGS-based tissue results for all key mutations showed positive percent agreement (PPA) of 85.3%. For individual genes, the PPA was as high as 95.7% for epidermal growth factor receptor (EGFR) mutations and 83.3% for ALK translocations. AlphaLiquid100 detected drug-sensitive EGFR mutation at a variant allele frequency as low as 0.02% and also identified an EGFR mutation in a case where tissue sample missed. Blood samples collected post-targeted therapies revealed additional acquired mutations. CONCLUSION: The AlphaLiquid100 ctDNA assay demonstrates robust analytical validity, offering clinically important information for NSCLC patients.

Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes for prediction of prognosis in resected colon cancer.

Tumor-infiltrating lymphocytes (TIL) have been suggested as an important prognostic marker in colorectal cancer, but assessment usually requires additional tissue processing and interpretational efforts. The aim of this study is to assess the clinical significance of artificial intelligence (AI)-powered spatial TIL analysis using only a hematoxylin and eosin (H&E)-stained whole-slide image (WSI) for the prediction of prognosis in stage II-III colon cancer treated with surgery and adjuvant therapy. In this retrospective study, we used Lunit SCOPE IO, an AI-powered H&E WSI analyzer, to assess intratumoral TIL (iTIL) and tumor-related stromal TIL (sTIL) densities from WSIs of 289 patients. The patients with confirmed recurrences had significantly lower sTIL densities (mean sTIL density 630.2/mm2 in cases with confirmed recurrence vs. 1021.3/mm2 in no recurrence, p < 0.001). Additionally, significantly higher recurrence rates were observed in patients having sTIL or iTIL in the lower quartile groups. Risk groups defined as high-risk (both iTIL and sTIL in the lowest quartile groups), low-risk (sTIL higher than the median), or intermediate-risk (not high- or low-risk) were predictive of recurrence and were independently associated with clinical outcomes after adjusting for other clinical factors. AI-powered TIL analysis can provide prognostic information in stage II/III colon cancer in a practical manner.

Cancer signature ensemble integrating cfDNA methylation, copy number, and fragmentation facilitates multi-cancer early detection.

Cell-free DNA (cfDNA) sequencing has demonstrated great potential for early cancer detection. However, most large-scale studies have focused only on either targeted methylation sites or whole-genome sequencing, limiting comprehensive analysis that integrates both epigenetic and genetic signatures. In this study, we present a platform that enables simultaneous analysis of whole-genome methylation, copy number, and fragmentomic patterns of cfDNA in a single assay. Using a total of 950 plasma (361 healthy and 589 cancer) and 240 tissue samples, we demonstrate that a multifeature cancer signature ensemble (CSE) classifier integrating all features outperforms single-feature classifiers. At 95.2% specificity, the cancer detection sensitivity with methylation, copy number, and fragmentomic models was 77.2%, 61.4%, and 60.5%, respectively, but sensitivity was significantly increased to 88.9% with the CSE classifier (p value < 0.0001). For tissue of origin, the CSE classifier enhanced the accuracy beyond the methylation classifier, from 74.3% to 76.4%. Overall, this work proves the utility of a signature ensemble integrating epigenetic and genetic information for accurate cancer detection.

Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes as a predictive biomarker for axitinib in adenoid cystic carcinoma.

BACKGROUND: This study analyzed the predictive value of artificial intelligence (AI)-powered tumor-infiltrating lymphocyte (TIL) analysis in recurrent or metastatic (R/M) adenoid cystic carcinoma (ACC) treated with axitinib. METHODS: Patients from a multicenter, prospective phase II trial evaluating axitinib efficacy in R/M ACC were included in this study. H&E whole-side images of archival tumor tissues were analyzed by Lunit SCOPE IO, an AI-powered spatial TIL analyzer. RESULTS: Twenty-seven patients were included in the analysis. The best response was stable disease, and the median progression-free survival (PFS) was 11.1 months (95% CI, 9.2-13.7 months). Median TIL densities in the cancer and surrounding stroma were 25.8/mm2 (IQR, 8.3-73.0) and 180.4/mm2 (IQR, 69.6-342.8), respectively. Patients with stromal TIL density >342.5/mm2 exhibited longer PFS (p = 0.012). CONCLUSIONS: Cancer and stromal area TIL infiltration were generally low in R/M ACC. Higher stromal TIL infiltration was associated with a longer PFS with axitinib treatment.

Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes as a biomarker in locally advanced unresectable thymic epithelial neoplasm: A single-center, retrospective, longitudinal cohort study.

BACKGROUND: Thymic epithelial tumors (TET) are rare malignancies and lack well-defined biomarkers for neoadjuvant therapy. This study aimed to evaluate the clinical utility of artificial intelligence (AI)-powered tumor-infiltrating lymphocyte (TIL) analysis in TET. METHODS: Patients initially diagnosed with unresectable thymoma or thymic carcinoma who underwent neoadjuvant therapy between January 2004 and December 2021 formed our study population. Hematoxylin and eosin-stained sections from the initial biopsy and surgery were analyzed using an AI-powered spatial TIL analyzer. Intratumoral TIL (iTIL) and stromal TIL (sTIL) were quantified and their immune phenotype (IP) was identified. RESULTS: Thirty-five patients were included in this study. The proportion of patients with partial response to neoadjuvant therapy was higher in the group with nondesert IP in preneoadjuvant biopsy (63.6% vs. 17.6%, p = 0.038). A significant increase in both iTIL (median 22.18/mm2 vs. 340.69/mm2 , p < 0.001) and sTIL (median 175.19/mm2 vs. 531.02/mm2 , p = 0.004) was observed after neoadjuvant therapy. Patients with higher iTIL (>147/mm2 ) exhibited longer disease-free survival (median, 29 months vs. 12 months, p = 0.009) and overall survival (OS) (median, 62 months vs. 45 months, p = 0.002). Patients with higher sTIL (>232.1/mm2 ) exhibited longer OS (median 62 months vs. 30 months, p = 0.021). CONCLUSIONS: Nondesert IP in initial biopsy was associated with a better response to neoadjuvant therapy. Increased infiltration of both iTIL and sTIL in surgical specimens were associated with longer OS in patients with TET who underwent resection followed by neoadjuvant therapy.

Spatial and clonality-resolved 3D cancer genome alterations reveal enhancer-hijacking as a potential prognostic marker for colorectal cancer.

The regulatory effect of non-coding large-scale structural variations (SVs) on proto-oncogene activation remains unclear. This study investigated SV-mediated gene dysregulation by profiling 3D cancer genome maps from 40 patients with colorectal cancer (CRC). We developed a machine learning-based method for spatial characterization of the altered 3D cancer genome. This revealed a frequent establishment of "de novo chromatin contacts" that can span multiple topologically associating domains (TADs) in addition to the canonical TAD fusion/shuffle model. Using this information, we precisely identified super-enhancer (SE)-hijacking and its clonal characteristics. Clonal SE-hijacking genes, such as TOP2B, are recurrently associated with cell-cycle/DNA-processing functions, which can potentially be used as CRC prognostic markers. Oncogene activation and increased drug resistance due to SE-hijacking were validated by reconstructing the patient's SV using CRISPR-Cas9. Collectively, the spatial and clonality-resolved analysis of the 3D cancer genome reveals regulatory principles of large-scale SVs in oncogene activation and their clinical implications.

Practical Utility of Liquid Biopsies for Evaluating Genomic Alterations in Castration-Resistant Prostate Cancer.

Traditional tissue-based assessments of genomic alterations in castration-resistant prostate cancer (CRPC) can be challenging. To evaluate the real-world clinical utility of liquid biopsies for the evaluation of genomic alterations in CRPC, we preemptively collected available plasma samples and archival tissue samples from patients that were being treated for clinically confirmed CRPC. The cell-free DNA (cfDNA) and tumor tissue DNA were analyzed using the AlphaLiquid®100-HRR panel. Plasma samples from a total of 87 patients were included in this study. Somatic mutations from cfDNA were detected in 78 (89.7%) patients, regardless of the presence of overt metastasis or concomitant treatment given at the time of plasma sample collection. Twenty-three patients were found to have known deleterious somatic or germline mutations in HRR genes from their cfDNA. Archival tissue samples from 33 (37.9%) patients were available for comparative analysis. Tissue sequencing was able to yield an NGS result in only 51.5% of the tissue samples. The general sensitivity of cfDNA for detecting somatic mutations in tissues was 71.8%, but important somatic/germline mutations in HRR genes were found to have a higher concordance (100%). Liquid biopsies can be a reasonable substitute for tissue biopsies in CRPC patients when evaluating genomic alterations.

Predicting the chemotherapeutic response of colorectal cancer liver metastasis using shear-wave elastography.

PURPOSE: The aim of this study was to assess the role of the shear-wave velocity (SWV) value in predicting chemotherapeutic response and progression-free survival (PFS) in patients with colorectal cancer liver metastasis (CRLM). METHODS: In this prospective single-center study, participants with CRLM scheduled for chemotherapy were enrolled between May 2018 and June 2021. SWV measurements were obtained using shear-wave elastography at the CRLM site before and after initiating chemotherapy. Based on the Response Evaluation Criteria in Solid Tumors, the participants were categorized by chemotherapeutic response into responders (complete remission and partial remission) and non-responders (stable disease and progressive disease). Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the performance of changes in SWV measurements in predicting the chemotherapeutic response of CRLM. In addition, a Cox proportional hazards model was used to identify variables associated with PFS. RESULTS: In total, 67 participants (40 men; mean age, 62.3±10.1 years) were enrolled, including 34 responders and 33 non-responders. The area under the ROC curve, sensitivity, and negative predictive value of the SWV measurement in predicting non-responders were 0.840, 97.0%, and 95.2%, respectively, using a cutoff value of a 13% decrease. Additionally, a change in SWV values was independently associated with PFS (hazard ratio, 1.020), non-responder status, and the presence of five or more CRLMs. CONCLUSION: A change in SWV values measured after chemotherapy demonstrated meaningful diagnostic performance in predicting non-responsiveness among patients with CRLM. Additionally, a change in SWV values was independently associated with PFS.

Personalised circulating tumour DNA assay with large-scale mutation coverage for sensitive minimal residual disease detection in colorectal cancer.

BACKGROUND: Postoperative minimal residual disease (MRD) detection using circulating-tumour DNA (ctDNA) requires a highly sensitive analysis platform. We have developed a tumour-informed, hybrid-capture ctDNA sequencing MRD assay. METHODS: Personalised target-capture panels for ctDNA detection were designed using individual variants identified in tumour whole-exome sequencing of each patient. MRD status was determined using ultra-high-depth sequencing data of plasma cell-free DNA. The MRD positivity and its association with clinical outcome were analysed in Stage II or III colorectal cancer (CRC). RESULTS: In 98 CRC patients, personalised panels for ctDNA sequencing were built from tumour data, including a median of 185 variants per patient. In silico simulation showed that increasing the number of target variants increases MRD detection sensitivity in low fractions (<0.01%). At postoperative 3-week, 21.4% of patients were positive for MRD by ctDNA. Postoperative positive MRD was strongly associated with poor disease-free survival (DFS) (adjusted hazard ratio 8.40, 95% confidence interval 3.49-20.2). Patients with a negative conversion of MRD after adjuvant therapy showed significantly better DFS (P < 0.001). CONCLUSION: Tumour-informed, hybrid-capture-based ctDNA assay monitoring a large number of patient-specific mutations is a sensitive strategy for MRD detection to predict recurrence in CRC.

Mutational evolution after chemotherapy-progression in metastatic colorectal cancer revealed by circulating tumor DNA analysis.

Emerging new mutations after treatment can provide clues to acquired resistant mechanisms. Circulating tumor DNA (ctDNA) sequencing has enabled noninvasive repeated tumor mutational profiling. We aimed to investigate newly emerging mutations in ctDNA after disease progression in metastatic colorectal cancer (mCRC). Blood samples were prospectively collected from mCRC patients receiving palliative chemotherapy before treatment and at radiological evaluations. ctDNA from pretreatment and progressive disease (PD) samples were sequenced with a next-generation sequencing panel targeting 106 genes. A total of 712 samples from 326 patients were analyzed, and 381 pretreatment and PD pairs (163 first-line, 85 second-line and 133 later-line [≥third-line]) were compared. New mutations in PD samples (mean 2.75 mutations/sample) were observed in 49.6% (189/381) of treatments. ctDNA samples from later-line had more baseline mutations (P = .002) and were more likely to have new PD mutations (adjusted odds ratio [OR] 2.27, 95% confidence interval [CI]: 1.40-3.69) compared to first-line. RAS/BRAF wild-type tumors were more likely to develop PD mutations (adjusted OR 1.87, 95% CI: 1.22-2.87), independent of cetuximab treatment. The majority of new PD mutations (68.5%) were minor clones, suggesting an increasing clonal heterogeneity after treatment. Pathways involved by PD mutations differed by the treatment received: MAPK cascade (Gene Ontology [GO]: 0000165) in cetuximab and regulation of kinase activity (GO: 0043549) in regorafenib. The number of mutations revealed by ctDNA sequencing increased during disease progression in mCRC. Clonal heterogeneity increased after chemotherapy progression, and pathways involved were affected by chemotherapy regimens.

Circulating Tumor DNA Dynamics and Treatment Outcome of Regorafenib in Metastatic Colorectal Cancer.

PURPOSE: Circulating tumor DNA (ctDNA) is emerging as a valuable non-invasive tool to identify tumor heterogeneity and tumor burden. This study investigated ctDNA dynamics in metastatic colorectal cancer patients treated with regorafenib. Materials and Methods: In this prospective biomarker study, plasma cell-free DNA (cfDNA) samples obtained at baseline, at the first response evaluation after 2 cycles of treatment, and at the time of progressive disease were sequenced using a targeted next-generation sequencing platform which included 106 genes. RESULTS: A total of 285 blood samples from 110 patients were analyzed. Higher baseline cfDNA concentration was associated with worse progression-free survival (PFS) and overall survival (OS). After 2 cycles of treatment, variant allele frequency (VAF) in the majority of ctDNA mutations decreased with a mean relative change of -31.6%. Decreases in the VAF of TP53, APC, TCF7L2, and ROS1 after 2 cycles of regorafenib were associated with longer PFS. We used the sum of VAF at each time point as a surrogate for the overall ctDNA burden. A reduction in sum (VAF) of ≥ 50% after 2 cycles was associated with longer PFS (6.1 vs. 2.7 months, p=0.002), OS (11.3 vs. 5.9 months, p=0.001), and higher disease control rate (86.3% vs. 51.1%, p < 0.001). VAF of the majority of the ctDNA mutations increased at the time of disease progression, and VAF of BRAF increased markedly. CONCLUSION: Reduction in ctDNA burden as estimated by sum (VAF) could be used to predict treatment outcome of regorafenib.

Efficacy of Olaparib in Treatment-Refractory, Metastatic Breast Cancer with Uncommon Somatic BRCA Mutations Detected in Circulating Tumor DNA.

Poly(ADP-ribose) polymerase inhibitors have been shown dramatic responses in patients with BRCAness. However, clinical studies have been limited to breast cancer patients with germline mutations. Here, we describe a patient with metastatic breast cancer who had a rare BRCA1 somatic mutation (BRCA1 c.4336G>T (p.E1446*)) detected by cell-free DNA analysis after failing standard therapies. This tier III variant of unknown significance was predicted to be a pathogenic variant in our assessment, leading us to consider off-label treatment with olaparib. The patient responded well to olaparib for several months, with a decrease in allele frequency of this BRCA1 somatic mutation in cell-free DNA. Olaparib resistance subsequently developed with an increase in the allele frequency and new BRCA1 reversion mutations. To our knowledge, this is the first report confirming BRCA1 c.4336G>T (p.E1446*) as a mutation sensitive to olaparib in breast cancer and describing the dynamic changes in the associated mutations using liquid biopsy.

Dynamic changes in longitudinal circulating tumour DNA profile during metastatic colorectal cancer treatment.

BACKGROUND: Circulating tumour DNA (ctDNA) has been spotlighted as an attractive biomarker because of its easy accessibility and real-time representation of tumour genetic profile. However, the clinical utility of longitudinal ctDNA monitoring has not been clearly defined. METHODS: Serial blood samples were obtained from metastatic colorectal cancer patients undergoing first-line chemotherapy. ctDNA was sequenced using a targeted next-generation sequencing platform which included 106 genes. Changes in ctDNA profile and treatment outcome were comprehensively analysed. RESULTS: A total of 272 samples from 62 patients were analysed. In all, 90.3% of patients had detectable ctDNA mutation before treatment. ctDNA clearance after chemotherapy was associated with longer progression-free survival which was independent of radiological response (adjusted hazard ratio 0.22, 95% confidence interval 0.10-0.46). Longitudinal monitoring was able to detect ctDNA progression which preceded radiological progressive disease (PD) in 58.1% (median 3.3 months). Diverse resistant mutations (34.9%) and gene amplification (7.0%) at the time of PD were discovered. For 16.3% of the PD patients, the newly identified mutations could be potential candidates of targeted therapy or clinical trial. CONCLUSION: ctDNA profile provided a more accurate landscape of tumour and dynamic changes compared to radiological evaluation. Longitudinal ctDNA monitoring may improve personalised treatment decision-making.

Circulating tumor DNA sequencing in colorectal cancer patients treated with first-line chemotherapy with anti-EGFR.

Circulating tumor DNA (ctDNA) may reveal dynamic tumor status during therapy. We conducted serial ctDNA analysis to investigate potential association with clinical outcome in metastatic colorectal cancer (mCRC) patients receiving chemotherapy. Tissue KRAS/NRAS wild-type mCRC patients were enrolled and treated with first-line cetuximab-containing chemotherapy. ctDNA isolated from plasma were analyzed by next generation sequencing (NGS) with 16 targeted gene panel. Among 93 patients, 84 (90.3%) had at least 1 somatic mutation in baseline ctDNA samples (average 2.74). Five patients with KRAS or NRAS hotspot mutation in the ctDNA showed significantly worse progression-free survival (PFS) (p = 0.029). Changes in average variant allele frequency (VAF) in ctDNA showed significant correlation with tumor size change at the time of first response evaluation (p = 0.020) and progressive disease (PD) (p = 0.042). Patients whose average VAF decreased below cutoff (< 1%) at the first evaluation showed significantly better PFS (p < 0.001), and the average VAF change further discriminated the PFS in the patients in partial response (p = 0.018). At the time of PD, 54 new mutations including KRAS and MAP2K1 emerged in ctDNA. ctDNA sequencing can provide mutation profile that could better reflect tumor mutation status and predict treatment outcome.

Phenotype-based single cell sequencing identifies diverse genetic subclones in CD133 positive cancer stem cells.

Tumor heterogeneity is one of the ongoing huddles in the field of colon cancer therapy. It is evident that there are countless clones which exhibit different phenotypes and therefore, single cell analysis is inevitable. Cancer stem cells (CSCs) are rare cell population within tumor which is known to function in cancer metastasis and recurrence. Although there have been trials to prove intra-tumoral heterogeneity using single cell sequencing, that of CSCs has not been clearly elucidated. Here, we articulate the presence of heterogeneous subclones within CD133 positive cancer stem cells through single cell sequencing. As a proof of principle, we performed phenotype-based high-throughput laser isolation and single cell sequencing (PHLI-seq) of CD133 positive cells in a frozen tumor tissue obtained from a patient with colorectal cancer. The result proved that CD133 positive cells were shown to be heterogeneous both in copy number and mutational profiles. Single cancer stem cell specific mutations such as RNF144A, PAK2, PARP4, ADAM21, HYDIN, KRT38 and CELSR1 could be also detected in liver metastatic tumor of the same patient. Collectively, these data suggest that single cell analysis used to spot subclones with genetic variation within rare population, will lead to new strategies to tackle colon cancer metastasis.

Immunogenicity of Influenza Vaccination in Patients with Cancer Receiving Immune Checkpoint Inhibitors.

Among prospectively enrolled adult patients with cancer receiving immune checkpoint inhibitors (ICIs; n = 46) or cytotoxic agents (n = 90), seroprotection and seroconversion rates after seasonal quadrivalent influenza vaccinations were higher with ICI than with cytotoxic chemotherapy. These results support annual influenza vaccinations for cancer patients receiving ICIs. Clinical Trials Registration clinicaltrials.gov (NCT03590808).