To find fault is easy, to find no-fault is fair.

The inequity of medical negligence-based adversarial litigation in the USA, UK and Australia is a recognised target for reform. Plaintiff autonomy is weakened by a dispute resolution system that has evolved around lawyers, opposed experts and indemnity insurers; the need to prove breach and causation excludes compensation for other categories of medical injury; and patient access to the system is restricted by high entry costs. Two strategies towards reform are raised here. A short-term approach involves routine initial use of a single court-appointed medical expert for assessment of errors and liabilities, thus improving access while relegating fault-finding to a reserve role. In the longer term, adversarial litigation could be replaced in part by a no-fault compensation scheme - such as in Scandinavia, France and New Zealand - funded by taxation and by re-directed medical indemnity fees. Reforms such as these would be challenging to implement, but are achievable, so it is not premature for relevant bodies to consider a timetable for action.

Synonymous alterations of cancer-associated Trp53 CpG mutational hotspots cause fatal developmental jaw malocclusions but no tumors in knock-in mice.

Intragenic CpG dinucleotides are tightly conserved in evolution yet are also vulnerable to methylation-dependent mutation, raising the question as to why these functionally critical sites have not been deselected by more stable coding sequences. We previously showed in cell lines that altered exonic CpG methylation can modify promoter start sites, and hence protein isoform expression, for the human TP53 tumor suppressor gene. Here we extend this work to the in vivo setting by testing whether synonymous germline modifications of exonic CpG sites affect murine development, fertility, longevity, or cancer incidence. We substituted the DNA-binding exons 5-8 of Trp53, the mouse ortholog of human TP53, with variant-CpG (either CpG-depleted or -enriched) sequences predicted to encode the normal p53 amino acid sequence; a control construct was also created in which all non-CpG sites were synonymously substituted. Homozygous Trp53-null mice were the only genotype to develop tumors. Mice with variant-CpG Trp53 sequences remained tumor-free, but were uniquely prone to dental anomalies causing jaw malocclusion (p < .0001). Since the latter phenotype also characterises murine Rett syndrome due to dysfunction of the trans-repressive MeCP2 methyl-CpG-binding protein, we hypothesise that CpG sites may exert non-coding phenotypic effects via pre-translational cis-interactions of 5-methylcytosine with methyl-binding proteins which regulate mRNA transcript initiation, expression or splicing, although direct effects on mRNA structure or translation are also possible.

Development and Validation of a Machine Learning Approach Leveraging Real-World Clinical Narratives as a Predictor of Survival in Advanced Cancer.

PURPOSE: Predicting short-term mortality in patients with advanced cancer remains challenging. Whether digitalized clinical text can be used to build models to enhance survival prediction in this population is unclear. MATERIALS AND METHODS: We conducted a single-centered retrospective cohort study in patients with advanced solid tumors. Clinical correspondence authored by oncologists at the first patient encounter was extracted from the electronic medical records. Machine learning (ML) models were trained using narratives from the derivation cohort, before being tested on a temporal validation cohort at the same site. Performance was benchmarked against Eastern Cooperative Oncology Group performance status (PS), comparing ML models alone (comparison 1) or in combination with PS (comparison 2), assessed by areas under receiver operating characteristic curves (AUCs) for predicting vital status at 11 time points from 2 to 52 weeks. RESULTS: ML models were built on the derivation cohort (4,791 patients from 2001 to April 2017) and tested on the validation cohort of 726 patients (May 2017-June 2019). In 441 patients (61%) where clinical narratives were available and PS was documented, ML models outperformed the predictivity of PS (mean AUC improvement, 0.039, P < .001, comparison 1). Inclusion of both clinical text and PS in ML models resulted in further improvement in prediction accuracy over PS with a mean AUC improvement of 0.050 (P < .001, comparison 2); the AUC was > 0.80 at all assessed time points for models incorporating clinical text. Exploratory analysis of oncologist's narratives revealed recurring descriptors correlating with survival, including referral patterns, mobility, physical functions, and concomitant medications. CONCLUSION: Applying ML to oncologists' narratives with or without including patient's PS significantly improved survival prediction to 12 months, suggesting the utility of clinical text in building prognostic support tools.

The secret identities of TMPRSS2: Fertility factor, virus trafficker, inflammation moderator, prostate protector and tumor suppressor.

The human TMPRSS2 gene is pathogenetically implicated in both coronaviral lung infection and prostate cancer, suggesting its potential as a drug target in both contexts. SARS-COV-2 spike polypeptides are primed by the host transmembrane TMPRSS2 protease, triggering virus fusion with epithelial cell membranes followed by an endocytotic internalisation process that bypasses normal endosomal activation of cathepsin-mediated innate immunity; viral co-opting of TMPRSS2 thus favors microbial survivability by attenuating host inflammatory responses. In contrast, most early hormone-dependent prostate cancers express TMPRSS2:ERG fusion genes arising from deletions that eliminate the TMPRSS2 coding region while juxtaposing its androgen-inducible promoter and the open reading frame of ERG, upregulating pro-inflammatory ERG while functionally disabling TMPRSS2. Moreover, inflammatory oxidative DNA damage selects for TMPRSS2:ERG-fused cancers, whereas patients treated with antiinflammatory drugs develop fewer of these fusion-dependent tumors. These findings imply that TMPRSS2 protects the prostate by enabling endosomal bypass of pathogens which could otherwise trigger inflammation-induced DNA damage that predisposes to TMPRSS2:ERG fusions. Hence, the high oncogenic selectability of TMPRSS2:ERG fusions may reflect a unique pro-inflammatory synergy between androgenic ERG gain-of-function and fusogenic TMPRSS2 loss-of-function, cautioning against the use of TMPRSS2-inhibitory drugs to prevent or treat early prostate cancer.

2b or Not 2b: How Opposing FGF Receptor Splice Variants Are Blocking Progress in Precision Oncology.

More than ten thousand peer-reviewed studies have assessed the role of fibroblast growth factors (FGFs) and their receptors (FGFRs) in cancer, but few patients have yet benefited from drugs targeting this molecular family. Strategizing how best to use FGFR-targeted drugs is complicated by multiple variables, including RNA splicing events that alter the affinity of ligands for FGFRs and hence change the outcomes of stromal-epithelial interactions. The effects of splicing are most relevant to FGFR2; expression of the FGFR2b splice isoform can restore apoptotic sensitivity to cancer cells, whereas switching to FGFR2c may drive tumor progression by triggering epithelial-mesenchymal transition. The differentiating and regulatory actions of wild-type FGFR2b contrast with the proliferative actions of FGFR1 and FGFR3, and may be converted to mitogenicity either by splice switching or by silencing of tumor suppressor genes such as CDH1 or PTEN. Exclusive use of small-molecule pan-FGFR inhibitors may thus cause nonselective blockade of FGFR2 isoforms with opposing actions, undermining the rationale of FGFR2 drug targeting. This splice-dependent ability of FGFR2 to switch between tumor-suppressing and -driving functions highlights an unmet oncologic need for isoform-specific drug targeting, e.g., by antibody inhibition of ligand-FGFR2c binding, as well as for more nuanced molecular pathology prediction of FGFR2 actions in different stromal-tumor contexts.

How aging of the global population is changing oncology.

Population aging is causing a demographic redistribution with implications for the future of healthcare. How will this affect oncology? First, there will be an overall rise in cancer affecting older adults, even though age-specific cancer incidences continue to fall due to better prevention. Second, there will be a wider spectrum of health functionality in this expanding cohort of older adults, with differences between "physiologically older" and "physiologically younger" patients becoming more important for optimal treatment selection. Third, greater teamwork with supportive care, geriatric, mental health and rehabilitation experts will come to enrich oncologic decision-making by making it less formulaic than it is at present. Success in this transition to a more nuanced professional mindset will depend in part on the development of user-friendly computational tools that can integrate a complex mix of quantitative and qualitative inputs from evidence-based medicine, functional and cognitive assessments, and the personal priorities of older adults.

Beyond BCG: the approaching era of personalised bladder-sparing therapies for non-muscle-invasive urothelial cancers.

Progress in the management of non-muscle invasive bladder cancer has been slow. Despite longstanding use of intravesical therapies (e.g., Bacille Calmette-Guerin; BCG) to complement cystoscopic resection of high-grade lesions, many patients still develop recurrences requiring cystectomy, while others suffer side-effects of BCG without definite benefit. Many questions remain: for example, how many patients receive intravesical prophylaxis without efficacy? Which high-risk patients are best managed with early cystectomy? Could systemic therapies and/or radiotherapy extend bladder preservation times? Such questions may soon be refined by clinicopathologic non-muscle invasive bladder cancer signatures that predict sensitivity to cytotoxic, immune and targeted therapies. Hypothesis-based trials using these signatures should lead to more rational adjuvant treatments, longer bladder preservation times, and better quality of life for patients.

Cancer Care Treatment Outcome Ontology: A Novel Computable Ontology for Profiling Treatment Outcomes in Patients With Solid Tumors.

PURPOSE: There is as yet no computer-processable resource to describe treatment end points in cancer, hindering our ability to systematically capture and share outcomes data to inform better patient care. To address these unmet needs, we have built an ontology, the Cancer Care Treatment Outcome Ontology (CCTOO), to organize high-level concepts of treatment end points with structured knowledge representation to facilitate standardized sharing of real-world data. METHODS: End points from oncology trials in ClinicalTrials.gov were extracted, queried using the keyword cancer, and followed by an expert appraisal. Synonyms and relevant terms were imported from the National Cancer Institute Thesaurus and Common Terminology Criteria for Adverse Events. Logical relationships among concepts were manually represented by production rules. The applicability of 1,847 rules was tested in an index case. RESULTS: After removing duplicated terms from 54,705 trial entries, an ontology holding 1,133 terms was built. CCTOO organized concepts into four domains (cancer treatment, health services, physical, and psychosocial health-related concepts), 13 subgroups (including efficacy, safety, and quality of life), and two (taxonomic and evaluative) concept hierarchies. This ontology has a comprehensive term coverage in the cancer trial literature: at least one term was mentioned in 98% of MEDLINE abstracts of phase I to III trials, whereas concepts about efficacy were mentioned in 7,208 (79%) phase I, 15,051 (92%) phase II, and 3,884 (86%) phase III trials. The event sequence of the index case was readily convertible to a comprehensive profile incorporating response, treatment toxicity, and survival by applying the set of production rules curated in the CCTOO. CONCLUSION: CCTOO categorizes high-level treatment end points used in oncology and provides a mechanism for profiling individual patient data by outcomes to facilitate translational analysis.

Thyroid cancer in a patient with Lynch syndrome - case report and literature review.

Lynch syndrome describes a familial cancer syndrome comprising germline mutations in one of four DNA mismatch repair genes, MLH1, MSH2, MSH6, and PMS2 and is characterized by colorectal, endometrial, and other epithelial malignancies. Thyroid cancer is not usually considered to be part of the constellation of Lynch syndrome cancers nor have Lynch syndrome tumor gene mutations been reported in thyroid malignancies. This study reports a woman with Lynch syndrome (colonic cancer and a DNA mismatch repair mutation in the MSH2 gene) with a synchronous papillary thyroid cancer. Six years later, she developed metachronous breast cancer. Metastatic bone disease developed after 3 years, and the disease burden was due to both breast and thyroid diseases. Despite multiple interventions for both metastatic breast and thyroid diseases, the patient's metastatic burden progressed and she died of leptomeningeal metastatic disease. Two prior case reports suggested thyroid cancer may be an extraintestinal malignancy of the Lynch syndrome cancer group. Hence, this study examined the genetic relationship between the patient's known Lynch syndrome and her thyroid cancer. The thyroid cancer tissue showed normal expression of MSH2, suggesting that the tumor was not due to the oncogenic mutation of Lynch syndrome, and molecular analysis confirmed BRAF V600E mutation. Although in this case the thyroid cancer was sporadic, it raises the importance of considering cancer genetics in familial cancer syndromes when other cancers do not fit the criteria of the syndrome. Careful documentation of other malignancies in patients with thyroid cancer and their families would assist in better understanding of any potential association. Appropriate genetic testing will clarify whether a common pathogenic mechanism links seemingly unrelated cancers.

TEPAPA: a novel in silico feature learning pipeline for mining prognostic and associative factors from text-based electronic medical records.

Vast amounts of clinically relevant text-based variables lie undiscovered and unexploited in electronic medical records (EMR). To exploit this untapped resource, and thus facilitate the discovery of informative covariates from unstructured clinical narratives, we have built a novel computational pipeline termed Text-based Exploratory Pattern Analyser for Prognosticator and Associator discovery (TEPAPA). This pipeline combines semantic-free natural language processing (NLP), regular expression induction, and statistical association testing to identify conserved text patterns associated with outcome variables of clinical interest. When we applied TEPAPA to a cohort of head and neck squamous cell carcinoma patients, plausible concepts known to be correlated with human papilloma virus (HPV) status were identified from the EMR text, including site of primary disease, tumour stage, pathologic characteristics, and treatment modalities. Similarly, correlates of other variables (including gender, nodal status, recurrent disease, smoking and alcohol status) were also reliably recovered. Using highly-associated patterns as covariates, a patient's HPV status was classifiable using a bootstrap analysis with a mean area under the ROC curve of 0.861, suggesting its predictive utility in supporting EMR-based phenotyping tasks. These data support using this integrative approach to efficiently identify disease-associated factors from unstructured EMR narratives, and thus to efficiently generate testable hypotheses.

Cancer and the omics revolution.

BACKGROUND: Internal medicine is in flux because of the 'omics revolution', with cancer medicine being a good example. Molecular technologies that detect alterations in gene-based structure or function are having an impact on diagnosis, prognosis and treatment of cancer. OBJECTIVE: In this article, recent advances in gene-based characterisation of cancer are presented, and illustrated where possible by clinical applications. DISCUSSION: The research-based vision of precision medicine is now on its way to becoming a clinical reality. A key limiting factor is the small number of therapeutic options available for customisation, which contrasts with the rising abundance of omics-derived data. However, further translational progress is anticipated over the next decade.

Computational prediction of multidisciplinary team decision-making for adjuvant breast cancer drug therapies: a machine learning approach.

BACKGROUND: Multidisciplinary team (MDT) meetings are used to optimise expert decision-making about treatment options, but such expertise is not digitally transferable between centres. To help standardise medical decision-making, we developed a machine learning model designed to predict MDT decisions about adjuvant breast cancer treatments. METHODS: We analysed MDT decisions regarding adjuvant systemic therapy for 1065 breast cancer cases over eight years. Machine learning classifiers with and without bootstrap aggregation were correlated with MDT decisions (recommended, not recommended, or discussable) regarding adjuvant cytotoxic, endocrine and biologic/targeted therapies, then tested for predictability using stratified ten-fold cross-validations. The predictions so derived were duly compared with those based on published (ESMO and NCCN) cancer guidelines. RESULTS: Machine learning more accurately predicted adjuvant chemotherapy MDT decisions than did simple application of guidelines. No differences were found between MDT- vs. ESMO/NCCN- based decisions to prescribe either adjuvant endocrine (97%, p = 0.44/0.74) or biologic/targeted therapies (98%, p = 0.82/0.59). In contrast, significant discrepancies were evident between MDT- and guideline-based decisions to prescribe chemotherapy (87%, p < 0.01, representing 43% and 53% variations from ESMO/NCCN guidelines, respectively). Using ten-fold cross-validation, the best classifiers achieved areas under the receiver operating characteristic curve (AUC) of 0.940 for chemotherapy (95% C.I., 0.922-0.958), 0.899 for the endocrine therapy (95% C.I., 0.880-0.918), and 0.977 for trastuzumab therapy (95% C.I., 0.955-0.999) respectively. Overall, bootstrap aggregated classifiers performed better among all evaluated machine learning models. CONCLUSIONS: A machine learning approach based on clinicopathologic characteristics can predict MDT decisions about adjuvant breast cancer drug therapies. The discrepancy between MDT- and guideline-based decisions regarding adjuvant chemotherapy implies that certain non-clincopathologic criteria, such as patient preference and resource availability, are factored into clinical decision-making by local experts but not captured by guidelines.

Damage-inducible intragenic demethylation of the human TP53 tumor suppressor gene is associated with transcription from an alternative intronic promoter.

Wild-type TP53 exons 5-8 contain CpG dinucleotides that are prone to methylation-dependent mutation during carcinogenesis, but the regulatory effects of methylation affecting these CpG sites are unclear. To clarify this, we first assessed site-specific TP53 CpG methylation in normal and transformed cells. Both DNA damage and cell ageing were associated with site-specific CpG demethylation in exon 5 accompanied by induction of a truncated TP53 isoform regulated by an adjacent intronic promoter (P2). We then synthesized novel synonymous TP53 alleles with divergent CpG content but stable encodement of the wild-type polypeptide. Expression of CpG-enriched TP53 constructs selectively reduced production of the full-length transcript (P1), consistent with a causal relationship between intragenic demethylation and transcription. 450K methylation comparison of normal (TP53-wildtype) and cancerous (TP53-mutant) human cells and tissues revealed focal cancer-associated declines in CpG methylation near the P1 transcription start site, accompanied by rises near the alternate exon 5 start site. These data confirm that site-specific changes of intragenic TP53 CpG methylation are extrinsically inducible, and suggest that human cancer progression is mediated in part by dysregulation of damage-inducible intragenic CpG demethylation that alters TP53 P1/P2 isoform expression. © 2015 The Authors. Molecular Carcinogenesis Published by Wiley Periodicals, Inc.

A periodic table for cancer.

Cancers exhibit differences in metastatic behavior and drug sensitivity that correlate with certain tumor-specific variables such as differentiation grade, growth rate/extent and molecular regulatory aberrations. In practice, patient management is based on the past results of clinical trials adjusted for these biomarkers. Here, it is proposed that treatment strategies could be fine-tuned upfront simply by quantifying tumorigenic spatial (cell growth) and temporal (genetic stability) control losses, as predicted by genetic defects of cell-cycle-regulatory gatekeeper and genome-stabilizing caretaker tumor suppressor genes, respectively. These differential quantifications of tumor dysfunction may in turn be used to create a tumor-specific 'periodic table' that guides rational formulation of survival-enhancing anticancer treatment strategies.

Lobular breast cancers lack the inverse relationship between ER/PR status and cell growth rate characteristic of ductal cancers in two independent patient cohorts: implications for tumor biology and adjuvant therapy.

BACKGROUND: Although invasive lobular carcinoma (ILC) of the breast differs from invasive ductal carcinoma (IDC) in numerous respects - including its genetics, clinical phenotype, metastatic pattern, and chemosensitivity - most experts continue to manage ILC and IDC identically in the adjuvant setting. Here we address this discrepancy by comparing early-stage ILC and IDC in two breast cancer patient cohorts of differing nationality and ethnicity. METHODS: The clinicopathologic features of 2029 consecutive breast cancer patients diagnosed in Hong Kong (HK) and Australia (AUS) were compared. Interrelationships between tumor histology and other clinicopathologic variables, including ER/PR and Ki67, were analysed. RESULTS: Two hundred thirty-nine patients were identified with ILC (11.8%) and 1790 patients with IDC. AUS patients were older (p <0.001) and more often postmenopausal (p <0.03) than HK patients. As expected, ILC tumors were lower in grade and proliferative rate, and more often ER-positive and HER2-negative, than IDC (p <0.002); yet despite this, ILC tumors were as likely as IDC to present with nodal metastases (p >0.7). Moreover, whereas IDC tumors exhibited a strongly negative relationship between ER/PR and Ki67 status (p <0.0005), ILC tumors failed to demonstrate any such inverse relationship (p >0.6). CONCLUSION: These data imply that the primary adhesion defect in ILC underlies a secondary stromal-epithelial disconnect between hormonal signaling and tumor growth, suggesting in turn that this peritumoral feedback defect could reduce both the antimetastatic (adjuvant) and tumorilytic (palliative) efficacy of cytotoxic therapies for such tumors. Hence, we caution against assuming similar adjuvant chemotherapeutic survival benefits for ILC and IDC tumors with similar ER and Ki67, whether based on immunohistochemical or gene expression assays.

Efficacy and tolerability of adjuvant oral capecitabine plus intravenous oxaliplatin (XELOX) in Asian patients with colorectal cancer: 4-year analysis.

BACKGROUND: Although FOLFOX (infusional fluorouracil/leucovorin plus oxaliplatin) is established as a standard chemotherapeutic regimen, the long term efficacy of adjuvant XELOX (oral capecitabine plus intravenous oxaliplatin) in Asian colorectal cancer (CRC) patients remains anecdotal. Moreover, uncertainties persist as to whether pharmacogenetic differences in Asian populations preclude equally tolerable and effective administration of these drugs. METHOD: One hundred consecutive patients with resected colorectal cancer received adjuvant XELOX (oxaliplatin 130 mg/m2 on day 1 plus capecitabine 900 mg/m2 twice daily on day 1 to 14 every 3 weeks for 8 cycles) at Queen Mary Hospital, Hong Kong. Endpoints monitored during follow-up were disease-free survival (DFS) and disease recurrence, overall survival (OS) and adverse events (AEs). RESULTS: The median patient age was 56 years, 56% were diagnosed with rectal cancer and 44% with colonic cancer. After a median follow-up of 4.3 years (95% confidence interval, 3.2-4.7), 24 recurrences were confirmed including 13 patients who died due to progressive disease. Four-year DFS was 81% in colon cancer patients and 67% in rectal cancer patients (p=0.06 by log-rank test). For the cohort as a whole, OS was 90% at 3 years and 84% at 5 years. Treatment-related AEs led to early withdrawal in four patients. The commonest non-hematological AEs were neuropathy (91%), hand-foot syndrome (49%) and diarrhea (46%), while the commonest grade 3/4 AEs were neutropenia (11%) and diarrhea (10%). CONCLUSION: These results confirm the favourable long term survival benefit with good tolerability in using adjuvant XELOX in treating East Asian colorectal cancer patients.