Both clinical and genomic data independently predict survival and treatment response in early-stage HER2-positive breast cancer. Here we present the development and validation of a new HER2DX risk score, and a new HER2DX pathological complete response (pCR) score, both based on a 27-gene expression plus clinical feature-based classifier. HER2DX is a supervised learning algorithm incorporating tumour size, nodal staging, and 4 gene expression signatures tracking immune infiltration, tumour cell proliferation, luminal differentiation, and the expression of the HER2 amplicon, into a single score. 434 HER2-positive tumours from the Short-HER trial were used to train a prognostic risk model; 268 cases from an independent cohort were used to verify the accuracy of the HER2DX risk score. In addition, 116 cases treated with neoadjuvant anti-HER2-based chemotherapy were used to train a predictive model of pathological complete response (pCR); two independent cohorts of 91 and 67 cases were used to verify the accuracy of the HER2DX pCR likelihood score. Five publicly available independent datasets with >1,000 patients with early-stage HER2-positive disease were also analysed. In Short-HER, HER2DX variables were associated with good risk outcomes (i.e., immune, and luminal) and poor risk outcomes (i.e., proliferation, and tumour and nodal staging). In an independent cohort, continuous HER2DX risk score was significantly associated with disease-free survival (DFS) (p=0·002); the 5-year DFS in the low-risk group was 97·4% (94·4-100·0%). For the neoadjuvant pCR predictor training cohort, HER2DX variables were associated with pCR (i.e., immune, proliferation and HER2 amplicon) and non-pCR (i.e., luminal, and tumour and nodal staging). In both independent test set cohorts, continuous HER2DX pCR likelihood score was significantly associated with pCR (p<0·0001). A weak negative correlation was found between the HER2DX risk score versus the pCR score (correlation coefficient -0·19). The two HER2DX tests provide accurate estimates of the risk of recurrence, and the likelihood to achieve a pCR, in early-stage HER2-positive breast cancer. This study received funding from Reveal Genomics, IDIBAPS and the University of Padova.

Mutations in the CDKN2A and CDK4 genes predispose to melanoma. From three case-control studies of cutaneous melanoma, we estimated the prevalence and predictors of these mutations for people from regions with widely differing latitudes and melanoma incidence. Population-based cases and controls from the United Kingdom (1586 cases, 499 controls) and Australia (596 early-onset cases, 476 controls), and a hospital-based series from Spain (747 cases, 109 controls), were screened for variants in all exons of CDKN2A and the p16INK4A binding domain of CDK4. The prevalence of mutations for people with melanoma was similar across regions: 2.3%, 2.5% and 2.0% for Australia, Spain and the United Kingdom respectively. The strongest predictors of carrying a mutation were having multiple primaries (odds ratio (OR) = 5.4, 95% confidence interval (CI: 2.5, 11.6) for 2 primaries and OR = 32.4 (95% CI: 14.7, 71.2) for 3 or more compared with 1 primary only); and family history (OR = 3.8; 95% CI:1.89, 7.5) for 1 affected first- or second-degree relative and OR = 23.2 (95% CI: 11.3, 47.6) for 2 or more compared with no affected relatives). Only 1.1% of melanoma cases with neither a family history nor multiple primaries had mutations. There is a low probability (<2%) of detecting a germline CDKN2A mutation in people with melanoma except for those with a strong family history of melanoma (≥2 affected relatives, 25%), three or more primary melanomas (29%), or more than one primary melanoma who also have other affected relatives (27%).

Monitoring of graft function is essential during the first months after liver transplantation (LT), but current liver function tests (LFTs) lack the specificity and sensitivity to ensure an efficient diagnosis of acute rejection (AR). Recently, donor‐derived cell‐free DNA (ddcfDNA) has emerged as a noninvasive biomarker to assess graft integrity. This study evaluated the feasibility of measuring the ddcfDNA through short tandem repeat (STR) analysis by quantitative fluorescent‐polymerase chain reaction (QF‐PCR) and to assess the role of the concentration and fragment size of total cfDNA as AR biomarkers. The total concentration and fragment size of cfDNA and the ddcfDNA percentage were monitored in plasma of 20 patients without rejection and 7 patients with T‐cell–mediated AR during the first 3 months after LT. The median ddcfDNA percentage was 3‐fold higher before AR diagnosis (34.8%; P < 0.001) and moderately higher at AR confirmatory diagnosis (23.8%; P = 0.049) compared with that of nonrejector patients (10.6%), showing a better performance (area under the curve = 84.6%) than conventional LFTs to predict the risk of rejection within the first 2 weeks following LT. The fraction of 100‐250‐bp cfDNA fragments was higher at AR diagnosis compared with that of nonrejector patients (68.0% versus 57.9%, P = 0.02). STR amplification by QF‐PCR may be an alternative strategy for rapid ddcfDNA quantification, which is easily implementable in clinical laboratories. The results of this pilot study indicate that ddcfDNA increases very early, even 1‐2 weeks before the diagnosis of AR, and so it could be useful as a prognostic biomarker in improving patient risk stratification.

Background Cutaneous melanoma tumour is classified into clinicohistopathological subtypes that may be associated with different genetic and host factors. Variation in the MC1R gene is one of the main factors of risk variation in sporadic melanoma. The relationship between MC1R variants and the risk of developing a specific subtype of melanoma has not been previously explored. Objectives To analyse whether certain MC1R variants are associated with particular melanoma subtypes with specific clinicohistopathological features. Methods An association study was performed between MC1R gene variants and clinicopathological subtypes of primary melanoma derived from 1679 patients. Results We detected 53 MC1R variants (11 synonymous and 42 nonsynonymous). Recurrent nonsynonymous variants were p.V60L (30·0%), p.V92M (11·7%), p.D294H (9·4%), p.R151C (8·8%), p.R160W (6·2%), p.R163Q (4·2%) p.R142H (3·3%), p.I155T (3·8%), p.V122M (1·5%) and p.D84E (1·0%). Melanoma subtypes showed differences in the total number of MC1R variants (P = 0·028) and the number of red hair colour variants (P = 0·035). Furthermore, an association between p.R163Q and lentigo maligna melanoma was detected under a dominant model of heritance (odds ratio 2·16, 95% confidence interval 1·07–4·37; P = 0·044). No association was found between p.R163Q and Fitzpatrick skin phototype, eye colour or skin colour, indicating that the association was independent of the role of MC1R in pigmentation. No association was observed between MC1R polymorphisms and other melanoma subtypes. Conclusions Our findings suggest that certain MC1R variants could increase melanoma risk due to their impact on pathways other than pigmentation, and may therefore be linked to specific melanoma subtypes.