Biomedical subjects

Sherene Loi

Publications and source records attributed to Sherene Loi.

12 recordsLinked to original sources

PubMed2026

Manual, digital, and AI tumour-infiltrating lymphocyte scoring: a secondary analysis of the APHINITY randomised trial.

BACKGROUND: Stromal tumour-infiltrating lymphocytes (sTILs) are prognostic in early-stage HER2-positive breast cancer, but their role in the context of dual HER2 blockade remains undefined. We evaluated manual, digital, and artificial intelligence (AI)-based sTIL quantification, together with AI-derived spatial metrics, for prognostic and treatment-benefit stratification using tumour samples from the phase 3 APHINITY trial. METHODS: In the APHINITY trial, 4805 patients were randomly assigned to receive chemotherapy plus trastuzumab with pertuzumab or chemotherapy plus trastuzumab with placebo. Median follow-up was 74·1 months (IQR 68·3-75·4). We analysed 4262 haematoxylin and eosin-stained images using manual assessment, an automated digital approach, AI-based lymphocyte quantification (AI percentage lymphocytes), and two AI-derived spatial features (AI-TIL and immune hotspot). Interobserver reproducibility was assessed in 262 randomly chosen tumour samples scored independently by five pathologists. Multivariable Cox models were used to assess associations between TIL levels and invasive disease-free survival (primary outcome in APHINITY), distant recurrence-free interval, and overall survival. The heterogeneity of pertuzumab benefit was evaluated using subgroup analyses, subpopulation treatment effect pattern plot analyses, and nested Cox models with treatment-by-biomarker interaction terms. FINDINGS: Manual scoring showed high interobserver reproducibility (intraclass correlation coefficient 0·84 [95% CI 0·79-0·88]). Concordance between manual and automated methods was modest. AI-based scoring (AI percentage lymphocytes) reclassified 120 (11·6%) of 1035 node-positive tumours from immune-low (by manual scoring) to immune-high; this subgroup of patients showed greater separation of 5-year invasive disease-free survival curves between pertuzumab and placebo groups compared with patients whose tumours were concordantly classified as immune-low by both manual and AI-based approaches. Higher levels of TILs were associated with improved invasive disease-free survival for all sTIL measurement approaches and spatial measurements (hazard ratios [HRs] 0·41-0·93). Pertuzumab was associated with improved invasive disease-free survival at higher sTIL levels across all measurement approaches (HRs 0·36-0·48), but was not associated with higher values of spatial measures. The largest 6-year absolute improvements with pertuzumab were observed in patients with node-positive disease whose tumours scored in the highest level of immune infiltration of manual sTIL scoring (≥70·0%; mean absolute improvement 12·1 percentage points [SD 2·8]). In nested prognostic and predictive models, AI-based immune hotspot scores provided the most consistent additional information when combined with any sTIL measurement (all p<0·010). INTERPRETATION: Standardised manual sTIL scoring was reproducible, and digital and AI-based methods showed consistent prognostic stratification and potential for treatment-benefit stratification despite only modest correlation between platforms. AI spatial metrics provided complementary information beyond sTIL density and could support more scalable immune assessment. Future studies are needed to validate these approaches in independent cohorts and to clarify their clinical utility for stratifying contemporary HER2-directed therapies. FUNDING: None.

Humans↗

PubMed2026

Artificial intelligence-based tumour infiltrating lymphocyte quantification in patients with triple-negative breast cancer: an independent validation study.

BACKGROUND: Tumour-infiltrating lymphocytes (TILs) are a robust prognostic marker in patients with triple-negative breast cancer. Artificial intelligence (AI)-derived computational tools assessing TILs could improve efficiency, but require independent validation against clinical outcomes. We aimed to compare the prognostic performance of AI-derived TIL scores with pathologist-scored TILs in a large, prospectively collected dataset pooled from randomised controlled trials. METHODS: CATALINA was an independent, external validation study using prospectively collected long-term clinical outcome data pooled from seven randomised clinical trials conducted at multiple sites. We independently evaluated two previously validated AI pipelines that generate five computationally assessed tumour-infiltrating lymphocyte (cTIL) scores by masked, independent deployment of locked models. cTIL scores were correlated with the mean of the pathologist-scored stromal TILs (sTILs) in 220 digitised haematoxylin and eosin whole slide images in a cohort of patients with early-stage triple-negative or HER-2 positive breast cancer, previously scored by trained pathologists in a TIL-reproducibility study. Prognostic performance was assessed in a separate cohort of patients with early triple-negative breast cancer pooled from seven prospective, randomised adjuvant trials. Multivariable Cox regression models adjusted for clinicopathological factors and study heterogeneity assessed associations of cTIL score and sTIL score with invasive disease-free survival, distant disease-free survival, and overall survival. 5-year discrimination was estimated using time-dependent area under the receiver operating characteristic curve (AUC). FINDINGS: Individual data were collated from 1759 patients, of whom 1356 had complete clinicopathological data, pathologist sTIL scores, and cTIL scores available. Modest correlation (r 0·375-0·473) was observed between cTIL scores and the mean pathologist sTIL score. Both sTIL and cTIL were independently associated with 5-year invasive disease-free survival, distant disease-free survival, and overall survival after adjustment for clinicopathological factors (hazard ratio for invasive disease-free survival was 0·73 [95% CI 0·66-0·82]; q<0·0001, distant disease-free survival was 0·70 [0·61-0·79]; q<0·0001, and overall survival was 0·72 [0·63-0·82]; q<0·0001 for sTIL scores and 0·80 [0·73-0·89]; q<0·0001, 0·77 [0·69-0·86]; q<0·0001, and 0·79 [0·70-0·88]; q=0·0002, respectively, for percentage_lymphocyte scores). In models adjusted for clinicopathological variables and sTIL score, cTIL score did not maintain a statistically significant prognostic association. Both sTIL and cTIL scores improved the 5-year AUC over clinicopathological variables alone, while cTIL score did not significantly further improve AUC when combined with clinicopathological variables and sTIL score. INTERPRETATION: Two cTIL models deployed entirely without retraining or modification provided statistically significant prognostic information and improved risk discrimination compared with clinicopathological variables alone in this large, platform-based, independent validation study. Although cTIL score did not incrementally improve prognostication compared with models combining clinicopathological variables with sTIL score, these findings support the application of cTILs as a reproducible prognostic biomarker, particularly in settings where routine or widespread pathologist assessment is unavailable. FUNDING: Breast Cancer Research Foundation (USA).

Humans↗

PubMed2006

The use of gene-expression profiling to better understand the clinical heterogeneity of estrogen receptor positive breast cancers and tamoxifen response.

In a short period of time DNA microarray technology has revolutionized our understanding of human cancer biology. This has been particularly impressive in the field of breast cancer research, where the clinical heterogeneity long observed by physicians seems to be mirrored by different molecular phenotypes exposed by microarray analysis. Gene-expression signatures have been developed to predict prognosis and treatment response and pending adequate validation, are on the verge of entry into the clinical setting. In this review article we explore how gene-expression profiling has influenced our understanding of the ER-positive breast cancers: that proliferation and cell-cycle genes seem to be the strongest predictor for metastasis and relapse in this group, and discuss the various gene predictors and molecular subtype classifications that exist that may help us individualize therapy for these women.

Biomarkers↗

PubMed2006

Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer.

BACKGROUND: A 70-gene signature was previously shown to have prognostic value in patients with node-negative breast cancer. Our goal was to validate the signature in an independent group of patients. METHODS: Patients (n = 307, with 137 events after a median follow-up of 13.6 years) from five European centers were divided into high- and low-risk groups based on the gene signature classification and on clinical risk classifications. Patients were assigned to the gene signature low-risk group if their 5-year distant metastasis-free survival probability as estimated by the gene signature was greater than 90%. Patients were assigned to the clinicopathologic low-risk group if their 10-year survival probability, as estimated by Adjuvant! software, was greater than 88% (for estrogen receptor [ER]-positive patients) or 92% (for ER-negative patients). Hazard ratios (HRs) were estimated to compare time to distant metastases, disease-free survival, and overall survival in high- versus low-risk groups. RESULTS: The 70-gene signature outperformed the clinicopathologic risk assessment in predicting all endpoints. For time to distant metastases, the gene signature yielded HR = 2.32 (95% confidence interval [CI] = 1.35 to 4.00) without adjustment for clinical risk and hazard ratios ranging from 2.13 to 2.15 after adjustment for various estimates of clinical risk; clinicopathologic risk using Adjuvant! software yielded an unadjusted HR = 1.68 (95% CI = 0.92 to 3.07). For overall survival, the gene signature yielded an unadjusted HR = 2.79 (95% CI = 1.60 to 4.87) and adjusted hazard ratios ranging from 2.63 to 2.89; clinicopathologic risk yielded an unadjusted HR = 1.67 (95% CI = 0.93 to 2.98). For patients in the gene signature high-risk group, 10-year overall survival was 0.69 for patients in both the low- and high-clinical risk groups; for patients in the gene signature low-risk group, the 10-year survival rates were 0.88 and 0.89, respectively. CONCLUSIONS: The 70-gene signature adds independent prognostic information to clinicopathologic risk assessment for patients with early breast cancer.

Adult↗

PubMed2006

Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis.

BACKGROUND: Histologic grade in breast cancer provides clinically important prognostic information. However, 30%-60% of tumors are classified as histologic grade 2. This grade is associated with an intermediate risk of recurrence and is thus not informative for clinical decision making. We examined whether histologic grade was associated with gene expression profiles of breast cancers and whether such profiles could be used to improve histologic grading. METHODS: We analyzed microarray data from 189 invasive breast carcinomas and from three published gene expression datasets from breast carcinomas. We identified differentially expressed genes in a training set of 64 estrogen receptor (ER)-positive tumor samples by comparing expression profiles between histologic grade 3 tumors and histologic grade 1 tumors and used the expression of these genes to define the gene expression grade index. Data from 597 independent tumors were used to evaluate the association between relapse-free survival and the gene expression grade index in a Kaplan-Meier analysis. All statistical tests were two-sided. RESULTS: We identified 97 genes in our training set that were associated with histologic grade; most of these genes were involved in cell cycle regulation and proliferation. In validation datasets, the gene expression grade index was strongly associated with histologic grade 1 and 3 status; however, among histologic grade 2 tumors, the index spanned the values for histologic grade 1-3 tumors. Among patients with histologic grade 2 tumors, a high gene expression grade index was associated with a higher risk of recurrence than a low gene expression grade index (hazard ratio = 3.61, 95% confidence interval = 2.25 to 5.78; P < .001, log-rank test). CONCLUSIONS: Gene expression grade index appeared to reclassify patients with histologic grade 2 tumors into two groups with high versus low risks of recurrence. This approach may improve the accuracy of tumor grading and thus its prognostic value.

Breast Neoplasms↗

PubMed2006

Molecular forecasting of breast cancer: time to move forward with clinical testing.

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Biomarkers, Tumor↗

PubMed2006

Gene signature evaluation as a prognostic tool: challenges in the design of the MINDACT trial.

This Review describes the work conducted by the TRANSBIG consortium in the development of the MINDACT (Microarray In Node negative Disease may Avoid ChemoTherapy) trial. The goal of the trial is to provide definitive evidence regarding the clinical relevance of the 70-gene prognosis signature, and to assess the performance of this signature compared with that of traditional prognostic indicators for assigning adjuvant chemotherapy to patients with node-negative breast cancer. We outline the background work and the key questions in node-negative early-stage breast cancer, and then focus on the MINDACT trial design and statistical considerations. The challenges inherent in this trial in terms of logistics, implementation and interpretation of the results are also discussed. We hope that this article will trigger further discussion about the difficulties of setting up and analyzing trials aimed at establishing the worth of new methods for better selection of patients for cancer treatment.

Breast Neoplasms↗

PubMed2005

Obesity and outcomes in premenopausal and postmenopausal breast cancer.

PURPOSE: Obesity is associated with adverse outcomes in postmenopausal women with breast cancer. In premenopausal women, the association is less clear. METHODS: A population-based sample of 1,360 Australian women with breast cancer before the age of 60 years, 47% diagnosed before age 40, and 74% premenopausal, was studied prospectively for a median of 5 years (range, 0.2-10.8 years). Obesity was defined as a body mass index of > or =30 kg/m2. The hazard ratio (HR) for adverse clinical outcome associated with obesity was estimated using Cox proportional hazard survival models. RESULTS: Obesity increased with age (P < 0.001) and was associated with increased breast cancer recurrence (P = 0.02) and death (P = 0.06), larger tumors (P = 0.002), and more involved axillary nodes (P = 0.003) but not with hormone receptor status (P > or = 0.6) or with first cycle adjuvant chemotherapy dose reductions (P = 0.1). Adjusting for number of axillary nodes, age at diagnosis, tumor size, grade, and hormone receptor status, obese women of all ages were more likely than nonobese women to have disease recurrence [HR, 1.57; 95% confidence interval (95% CI), 1.11-2.22; P = 0.02] and to die from any cause during follow-up (HR, 1.56; 95% CI, 1.01-2.40; P = 0.05). In premenopausal women, the adjusted HRs were 1.50 (95% CI, 1.00-2.26; P = 0.06) and 1.71 (95% CI, 1.05-2.77; P = 0.04), respectively. CONCLUSIONS: Obesity is independently associated with poorer outcomes in premenopausal women, as it is in postmenopausal women, and this is not entirely explained by differences in tumor size or nodal status. Given the high and increasing prevalence of obesity in western countries, more research on improving the treatment of obese breast cancer patients is warranted.

Adult↗

PubMed2005

Breast cancer gene expression profiling: clinical trial and practice implications.

The advent of high-throughput array-based technology and the sequencing of the human genome has provided the opportunity to begin comprehensive molecular and genetic profiling of cancers. Such efforts have, in a limited time, given us new insights into breast cancer biology and confirmed that the disease is considerably more heterogeneous than can be predicted by traditional histopathological methods. The estrogen receptor has been found to be the most dominant factor influencing the molecular composition of breast cancer and, in addition, novel subgroups of breast cancer with differing clinical outcomes have been observed. These may have substantial management implications for breast cancer patients and facilitate individualized rather than empirical oncological prescription. Furthermore, new methods of prognostic classification have been developed using array technology. The challenges ahead lie in refining the use of the technology, proper validation of discoveries, and the large-scale collaborative efforts necessary for the incorporation of genomic knowledge into the design and conduct of clinical trials. This will lead, ultimately, to the application of user-friendly tools derived from this technology to everyday patient care.

Biomarkers, Tumor↗

PubMed2004

A randomized cross-over trial to determine the effect of Cremophor EL on the pharmacodynamics and pharmacokinetics of carboplatin chemotherapy.

PURPOSE: Paclitaxel, when combined with carboplatin, exhibits a platelet-sparing effect. Paclitaxel is formulated in Cremophor EL (CrEL), which has been shown in preclinical models to reduce haematological toxicity from radiotherapy and chemotherapy. We sought to determine the effect of a 3-h infusion of 20 ml/m2 (equivalent to 175 mg/m2 paclitaxel) CrEL on myelosuppression following carboplatin chemotherapy, and the effect of CrEL on carboplatin pharmacokinetics. METHODS: A total of 16 patients with locally advanced or metastatic cancer were randomized to receive either CrEL or saline over 3 h prior to carboplatin (area under the curve, AUC, 5-7). Each patient was subsequently crossed over to the other treatment. Blood samples were collected at selected time-points for estimation of platinum AUC and 24-h platinum levels. Full blood counts were obtained three times per week. RESULTS: Of the 16 patients randomized, 15 were evaluable. Myelosuppression was measured by percentage fall at nadir and nadir levels. No significant differences were obtained when comparing CrEL and saline with respect to the above end-points after adjusting for multiple testing. There was no evidence to indicate that CrEL altered the pharmacokinetics of carboplatin. CONCLUSION: CrEL at this dose and schedule does not appear to be a major contributory factor to the platelet-sparing effect of paclitaxel when combined with carboplatin, nor does it alter the pharmacokinetics of carboplatin.

Adult↗

PubMed2004

Challenges in breast cancer clinical trial design in the postgenomic era.

PURPOSE OF REVIEW: Clinical trials in breast cancer (BC) have seldom taken into consideration molecular heterogeneity, because most have been performed in unselected populations. Hence, their results provide an estimated average benefit for the entire BC population, which may not always be translated to subsets of patients with certain characteristics, let alone to individual patients. Further understanding and acknowledgment of heterogeneity is vital for the development of individualized therapy in BC. New approaches are needed for trial design, patient selection, and choice of endpoints (including surrogate markers). The neoadjuvant setting presents a unique opportunity to test new concepts in a previously untreated patient population, because they may yield preliminary answers in a shorter time than that required in adjuvant trials. RECENT FINDINGS: The importance of patient selection in the development of targeted agents is exemplified by trastuzumab in BC and of gefitinib in lung cancer. Ongoing innovative trials that investigate biologic hypotheses include the BIG-EORTC p53, TOP and FRAGRANCE trials (which study predictive factors for response), and the NNBC-3 and MINDACT trials (which study prognostic factors). SUMMARY: There is an urgent need to break from traditional clinical development and to incorporate new molecular knowledge and translational research in the design of clinical trials. The success of new approaches in BC research critically depends on well-conducted translational research linked to prospective clinical trials, and international collaboration, bringing together human and technological resources.

Breast Neoplasms↗

PubMed2004

Glomerulosclerosis: a paraneoplastic phenomenon?

Glomerulosclerosis is not classically considered a paraneoplastic glomerular lesion. Focal and segmental glomerulosclerosis (FSGS) has rarely been reported in association with solid tumours. We report three cases of FSGS and an additional case of collapsing glomerulosclerosis in patients presenting with nephrotic syndrome and malignancy.

Adult↗