Cathal O'BRien

Poly(ADP-ribose) polymerase inhibitors (PARPi) have revolutionized the management of BRCA1- and BRCA2-associated ovarian cancer (OC). In 2020, Ireland implemented a nationwide, oncology-led pathway for mainstreamed BRCA1/2 testing in patients with OC. This study evaluated the pathway and characterised the BRCA1/2 landscape in an Irish cohort of patients with OC. Samples collected between January 2020 and December 2023 were tested in two national molecular diagnostic laboratories. Single-molecule molecular inversion probe sequencing was used to detect single nucleotide variants, while multiplex ligation-dependent probe amplification assessed large genomic rearrangements. Variants were classified according to the American College of Medical Genetics and Genomics and Association for Clinical Genomic Science 2020 guidelines and CanVIG-UK specifications. In total, 535 patients were included, with a median age of 65.5 years (range, 27–89 years). Of these, 455/535 (85.0%) underwent germline BRCA1/2 (gBRCA) testing using peripheral blood, and 360/535 (67.2%) underwent tumour BRCA1/2 (tBRCA) testing, resulting in 292/535 (54.6%) patients having paired testing. Among gBRCA-tested patients, 10.3% (47/455) had a clinically actionable variant (CAV), while 2.1% (10/455) had a variant of uncertain significance. Of the 262 patients who underwent paired testing and had negative gBRCA results, 9.5% (25/262) had a somatic BRCA CAV. Recurrent germline BRCA CAVs were identified in regional clusters, including BRCA1 c.5266dup, BRCA1 c.1175_1214del, and BRCA2 c.4398_4402del. This nationwide real-world study demonstrates that mainstreamed germline and somatic BRCA1/2 testing is feasible in Ireland and reports the prevalence of BRCA CAVs in a cohort of patients with OC. Although the observed prevalence of germline BRCA CAVs was lower than anticipated, it is consistent with UK real-world data. The identification of recurrent, regionally clustered germline variants further enhances the characterisation of the Irish genomic landscape.

Supplementary Table 1. All validation results and evaluation of intratumoral heterogeneity.

Purpose:Mismatch repair (MMR) deficiency and microsatellite instability are predictive biomarkers for immunotherapy response. The best approach to identify patients with such tumors is unclear in prostate cancer.Experimental Design:This study included 1,016 men diagnosed with primary prostate cancer during prospective follow-up of the Health Professionals Follow-up Study and Physicians’ Health Study. The highest-grade/index lesions from radical prostatectomy (95%) or transurethral resections of the prostate were mounted on tissue microarrays. Scoring of immunohistochemistry for the MMR proteins MLH1, MSH2, MSH6, and PMS2 required a nontumor internal positive control for designating deficiency. Validation was done on full sections and with PCR-based quantification of microsatellite repeats.Results:Tumor stage was predominantly pathologically localized with a full distribution of Gleason scores. MMR tumor scoring could be performed with available internal positive control tissue in 75% to 90% of cases, depending on the MMR protein. Of the 903 tumors evaluable for MSH2 protein loss, 4 tumors had loss of MSH2 (prevalence, 0.4%; 95% confidence interval, 0.2%–1.1%), and 3 of 708 evaluable tumors had concomitant loss of MSH6 (prevalence, 0.4%; 95% confidence interval, 0.1%–1.2%). No tumor had loss of MLH1 or PMS2. The four MMR-deficient cases had higher Gleason scores, and three had non-zero microsatellite repeats.Conclusions:In this nationwide prospective study, MMR deficiency was rare in primary, surgically treated prostate cancer. The low prevalence and the need for an internal positive control for this assay are feasibility concerns for unselected routine immunohistochemistry-based screening for MMR deficiency on limited tissue specimens, such as prostate biopsies.

Purpose HPV driven oropharyngeal squamous cell carcinoma (OPSCC) proffers a more favorable prognosis in contrast to its HPV negative counterparts. Consequently, studies have analyzed de-intensification measures of current treatment practices to minimize the associated morbidity. However, 25% of patients with HPV positive OPSCC experience a locoregional recurrence (LR) and/or distant metastasis (DM). This study aimed to determine if patient demographics, tumor characteristics and specific HPV genotyping were attributable to HPV positive OPSCC who develop LR and/or DM based on data collated from the largest Head and Neck Cancer center in the Republic of Ireland, with a mean follow up period of 11.16 years. Methods Patient demographics was obtained from HPV positive OPSCC patients from 3 Dublin Hospitals diagnosed over a 10-year period. In addition, HPV genotyping via Ion Torrent Next Generation Sequencing (NGS) and mutations analysis using smMIP panel based NGS was conducted on the cohort archival tumor DNA. Results 67 patients met the criteria for inclusion and had a mean follow-up period of 11.16 years. 28.36% developed LR and/or DM. A statistically significant correlation was identified linking age at diagnosis (p = 0.047), excessive alcohol consumption (p = 0.017) and a higher clinical stage (p = 0.01) with LR and/or DM.HPV 16 was the most prevalent genotype (93.65%), with dual HPV infection illustrated in 4 cases. BRAF, EGFR, ERBB2, KIT, KRAS, NRAS, PDGFRA somatic mutations were not identified in the recurrence cohort. Conclusion With the ongoing focus to reduce treatment for patient with HPV positive OPSCC, upfront recognition of patients at greater risk of LR and/or DM is essential. In the era of personalized medicine, it is hoped that interrogation of archival tumor tissue via similar techniques used in this study may yield pioneering findings with a clinical and prognostic significance.

Supplementary Table 1. All validation results and evaluation of intratumoral heterogeneity.

Purpose: Mismatch repair (MMR) deficiency and microsatellite instability are predictive biomarkers for immunotherapy response. The best approach to identify patients with such tumors is unclear in prostate cancer. Experimental Design: This study included 1,016 men diagnosed with primary prostate cancer during prospective follow-up of the Health Professionals Follow-up Study and Physicians’ Health Study. The highest-grade/index lesions from radical prostatectomy (95%) or transurethral resections of the prostate were mounted on tissue microarrays. Scoring of immunohistochemistry for the MMR proteins MLH1, MSH2, MSH6, and PMS2 required a nontumor internal positive control for designating deficiency. Validation was done on full sections and with PCR-based quantification of microsatellite repeats. Results: Tumor stage was predominantly pathologically localized with a full distribution of Gleason scores. MMR tumor scoring could be performed with available internal positive control tissue in 75% to 90% of cases, depending on the MMR protein. Of the 903 tumors evaluable for MSH2 protein loss, 4 tumors had loss of MSH2 (prevalence, 0.4%; 95% confidence interval, 0.2%–1.1%), and 3 of 708 evaluable tumors had concomitant loss of MSH6 (prevalence, 0.4%; 95% confidence interval, 0.1%–1.2%). No tumor had loss of MLH1 or PMS2. The four MMR-deficient cases had higher Gleason scores, and three had non-zero microsatellite repeats. Conclusions: In this nationwide prospective study, MMR deficiency was rare in primary, surgically treated prostate cancer. The low prevalence and the need for an internal positive control for this assay are feasibility concerns for unselected routine immunohistochemistry-based screening for MMR deficiency on limited tissue specimens, such as prostate biopsies.

The liquid biopsy has the potential to improve patient care in the diagnostic and therapeutic setting in non-small cell lung cancer (NSCLC). Consented patients with epidermal growth factor receptor (EGFR) positive disease (n = 21) were stratified into two cohorts: those currently receiving EGFR tyrosine kinase inhibitor (TKI) therapy (n = 9) and newly diagnosed EGFR TKI treatment-naïve patients (n = 12). Plasma genotyping of cell-free DNA was carried out using the FDA-approved cobas^® EGFR mutation test v2 and compared to next generation sequencing (NGS) cfDNA panels. Circulating tumor cell (CTC) numbers were correlated with treatment response and EGFR exon 20 p.T790M. The prognostic significance of the neutrophil to lymphocyte ratio (NLR) and lactate dehydrogenase (LDH) was also investigated. Patients in cohort 1 with an EGFR exon 20 p.T790M mutation progressed more rapidly than those with an EGFR sensitizing mutation, while patients in cohort 2 had a significantly longer progression-free survival (p = 0.04). EGFR exon 20 p.T790M was detected by liquid biopsy prior to disease progression indicated by computed tomography (CT) imaging. The cobas^® EGFR mutation test detected a significantly greater number of exon 20 p.T790M mutations (p = 0.05). High NLR and derived neutrophil to lymphocyte ratio (dNLR) were associated with shorter time to progression and worse survival outcomes (p < 0.05). High LDH levels were significantly associated with shorter time to disease progression (p = 0.03). These data support the use of liquid biopsy for monitoring EGFR mutations and inflammatory markers as prognostic indicators in NSCLC.

Advanced diagnostics are enabling cancer treatments to become increasingly tailored to the individual through developments in immunotherapies and targeted therapies. However, long turnaround times and high costs of molecular testing hinder the widespread implementation of targeted cancer treatments. Meanwhile, gold-standard histopathological assessment carried out by a trained pathologist is widely regarded as routine and mandatory in most cancers. Recently, methods have been developed to mine hidden information from histopathological slides using deep learning applied to scanned and digitized slides; deep learning comprises a collection of computational methods which learn patterns in data in order to make predictions. Such methods have been reported to be successful in a variety of cancers for predicting the presence of biomarkers such as driver mutations, tumour mutational burden, and microsatellite instability. This information could prove valuable to pathologists and oncologists in clinical decision making for cancer treatment and triage for in-depth sequencing. In addition to identifying molecular features, deep learning has been applied to predict prognosis and treatment response in certain cancers. Despite reported successes, many challenges remain before the clinical implementation of such diagnostic strategies in the clinical setting is possible. This review aims to outline recent developments in the field of deep learning for predicting molecular genetics from histopathological slides, as well as to highlight limitations and pitfalls of working with histopathology slides in deep learning.