A prediction model for response to immune checkpoint inhibition in advanced melanoma

Predicting who will benefit from treatment with immune checkpoint inhibition (ICI) in patients with advanced melanoma is challenging. We developed a multivariable prediction model for response to ICI, using routinely available clinical data including primary melanoma characteristics. We used a population-based cohort of 3525 patients with advanced cutaneous melanoma treated with anti-PD-1-based therapy. Our prediction model for predicting response within 6 months after ICI initiation was internally validated with bootstrap resampling. Performance evaluation included calibration, discrimination and internal-external cross-validation. Included patients received anti-PD-1 monotherapy (n = 2366) or ipilimumab plus nivolumab (n = 1159) in any treatment line. The model included serum lactate dehydrogenase, World Health Organization performance score, type and line of ICI, disease stage and time to first distant recurrence-all at start of ICI-, and location and type of primary melanoma, the presence of satellites and/or in-transit metastases at primary diagnosis and sex. The over-optimism adjusted area under the receiver operating characteristic was 0.66 (95% CI: 0.64-0.66). The range of predicted response probabilities was 7%-81%. Based on these probabilities, patients were categorized into quartiles. Compared to the lowest response quartile, patients in the highest quartile had a significantly longer median progression-free survival (20.0 vs 2.8 months; P < .001) and median overall survival (62.0 vs 8.0 months; P < .001). Our prediction model, based on routinely available clinical variables and primary melanoma characteristics, predicts response to ICI in patients with advanced melanoma and discriminates well between treated patients with a very good and very poor prognosis.

Pros and cons of artificial intelligence implementation in diagnostic pathology

The rapid introduction of digital pathology has greatly facilitated development of artificial intelligence (AI) models in pathology that have shown great promise in assisting morphological diagnostics and quantitation of therapeutic targets. We are now at a tipping point where companies have started to bring algorithms to the market, and questions arise whether the pathology community is ready to implement AI in routine workflow. However, concerns also arise about the use of AI in pathology. This article reviews the pros and cons of introducing AI in diagnostic pathology.

Re-attendance in supplemental breast MRI screening rounds of the DENSE trial for women with extremely dense breasts

OBJECTIVES

Supplemental MRI screening improves early breast cancer detection and reduces interval cancers in women with extremely dense breasts in a cost-effective way. Recently, the European Society of Breast Imaging recommended offering MRI screening to women with extremely dense breasts, but the debate on whether to implement it in breast cancer screening programs is ongoing. Insight into the participant experience and willingness to re-attend is important for this discussion.

METHODS

We calculated the re-attendance rates of the second and third MRI screening rounds of the DENSE trial. Moreover, we calculated age-adjusted odds ratios (ORs) to study the association between characteristics and re-attendance. Women who discontinued MRI screening were asked to provide one or more reasons for this.

RESULTS

The re-attendance rates were 81.3% (3458/4252) and 85.2% (2693/3160) in the second and third MRI screening round, respectively. A high age (> 65 years), a very low BMI, lower education, not being employed, smoking, and no alcohol consumption were correlated with lower re-attendance rates. Moderate or high levels of pain, discomfort, or anxiety experienced during the previous MRI screening round were correlated with lower re-attendance rates. Finally, a plurality of women mentioned an examination-related inconvenience as a reason to discontinue screening (39.1% and 34.8% in the second and third screening round, respectively).

CONCLUSIONS

The willingness of women with dense breasts to re-attend an ongoing MRI screening study is high. However, emphasis should be placed on improving the MRI experience to increase the re-attendance rate if widespread supplemental MRI screening is implemented.

CLINICAL RELEVANCE STATEMENT

For many women, MRI is an acceptable screening method, as re-attendance rates were high - even for screening in a clinical trial setting. To further enhance the (re-)attendance rate, one possible approach could be improving the overall MRI experience.

KEY POINTS

• The willingness to re-attend in an ongoing MRI screening study is high. • Pain, discomfort, and anxiety in the previous MRI screening round were related to lower re-attendance rates. • Emphasis should be placed on improving MRI experience to increase the re-attendance rate in supplemental MRI screening.

Integration of pathological criteria and immunohistochemical evaluation for invasive lobular carcinoma diagnosis: recommendations from the European Lobular Breast Cancer Consortium

Invasive lobular carcinoma (ILC) is the second most frequent type of breast cancer (BC) and its peculiar morphology is mainly driven by inactivation of CDH1, the gene coding for E-cadherin cell adhesion protein. ILC-specific therapeutic and disease-monitoring approaches are gaining momentum in the clinic, increasing the importance of accurate ILC diagnosis. Several essential and desirable morphological diagnostic criteria are currently defined by the World Health Organization, the routine use of immunohistochemistry (IHC) for E-cadherin is not recommended. Disagreement in the diagnosis of ILC has been repeatedly reported, but inter-pathologist agreement increases with the use of E-cadherin IHC. In this study, we aimed to harmonize the pathological diagnosis of ILC by comparing five commonly used E-cadherin antibody clones (NCH-38, EP700Y, Clone 36, NCL-L-E-cad [Clone 36B5], and ECH-6). We determined their biochemical specificity for the E-cadherin protein and IHC staining performance according to type and location of mutation on the CDH1 gene. Western blot analysis on mouse cell lines with conditional E-cadherin expression revealed a reduced specificity of EP700Y and NCL-L-E-cad for E-cadherin, with cross-reactivity of Clone 36 to P-cadherin. The use of IHC improved inter-pathologist agreement both for ILC as well as for lobular carcinoma in situ and atypical lobular hyperplasia. The E-cadherin IHC staining pattern was associated with variant allele frequency and likelihood of non-sense mediated RNA decay but not with the type or position of CDH1 mutations. Based on these results, we make recommendations for the indication for E-cadherin staining, choice of antibodies, and their interpretation in order to standardize ILC diagnosis in current pathology practice.

Breast tissue imaging atlas using ultra-fast confocal microscopy to identify cancer lesions

New generation ultra-fast fluorescence confocal microscopy (UFCM) allows to image histological architecture of fresh breast tissue and may be used for ex vivo intraoperative analysis for margin status. The criteria to identify breast tumoral and non-tumoral tissues in UFCM images are still objects of investigation. The objective of the study was to create an atlas of ex vivo UFCM images of breast tissues and breast carcinomas based on the first extensive collection of large field-of-view UFCM breast images. One hundred sixty patients who underwent conserving surgery for breast cancer were included. Their fresh surgical specimens were sliced, stained with acridine orange, and imaged at high resolution with large-field-of-view UFCM. The resulting images were digitally false colored to resemble frozen sections. Each UFCM image was correlated with the corresponding definitive histology. Representative images of normal tissue, inflammation, benign lesions, invasive carcinoma (IC), and ductal carcinoma in situ (DCIS) were collected. A total of 320 large-field images were recorded from 58 IC of no special type, 44 invasive lobular carcinomas, 1 invasive mucinous carcinoma, 47 DCIS, 2 lobular carcinomas in situ, and 8 specimens without cancer. Representative images of the main components of the normal breast and the main types of ICs and DCIS were annotated to establish an UFCM atlas. UFCM enables the imaging of the fresh breast tissue sections. Main morphological criteria defined in traditional histopathology such as tissue architecture and cell features can be applied to describe UFCM images content. The generated atlas of the main normal or tumoral tissue features will support the adoption of this optical technology for the intraoperative examination of breast specimens in clinical practice as it can be used to train physicians on UFCM images and develop artificial intelligence algorithms. Further studies are needed to document rare breast lesions.

Intertumoral heterogeneity of bifocal breast cancer: a morphological and molecular study

PURPOSE

To analyze concordance rates between individual foci of bifocal BC for histological grade, type and intrinsic subtype based on immunohistochemical (IHC) and mRNA-testing using MammaTyper.

METHODS

We evaluated histological grade and type as well as intrinsic subtype based on IHC status for estrogen and progesterone receptors, HER2 and the mitotic activity index in 158 individual foci of 79 bifocal BC. A subgroup of 31 cases additionally underwent mRNA-based subtyping using the MammaTyper (MT) test. We calculated concordance rates between individual foci, as well as Cohen's Kappa (K).

RESULTS

For 79 bifocal BC, concordance rates between individual foci for grade, histological type, and IHC-based subtype were 69.6% (K=0.53), 92.4% (K=0.81), and 74.7% (K=0.62), respectively. In the MT subgroup of 31 bifocal BC, concordance rates between individual foci for grade, histological type, IHC-based and mRNA-based intrinsic subtype were 87.1% (K=0.78), 90.3% (K=0.73), 87.1% (K=0.82), and 87.1% (K=0.7), respectively. Overall concordance between IHC- and mRNA-based subtype in the MT subgroup was 79% (K=0.7). In 6/79 cases (7.6%), testing of the smaller focus added clinically relevant information either on IHC- or mRNA-level: four cases showed high hormonal receptor expression while the expression in the larger focus was negative or low, warranting additional endocrine treatment; two cases presented with higher proliferative activity in the smaller focus, warranting additional chemotherapy.

CONCLUSION

In bifocal BC, intertumoral heterogeneity on the morphological, immunohistochemical and molecular level is common, with discordant intrinsic subtype in up to 25% between individual foci, with about 8% clinically relevant discordances.

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

The difficulty with measuring the largest melanoma tumour diameter in sentinel lymph nodes

Identification of sentinel node (SN) metastases can set the adjuvant systemic therapy indication for stage III melanoma patients. For stage IIIA patients, a 1.0 mm threshold for the largest SN tumour diameter is used. Therefore, uniform reproducible measurement of its size is crucial. At present, the number of deposits or their microanatomical sites are not part of the inclusion criteria for adjuvant treatment. The goal of the current study was to show examples of the difficulty of measuring SN melanoma tumour diameter and teach how it should be measured. Histopathological slides of SN-positive melanoma patients were retrieved using the Dutch Pathology Registry (PALGA). Fourteen samples with the largest SN metastasis around 1.0 mm were uploaded via tele-pathology and digitally measured by 12 pathologists to reflect current practice of measurements in challenging cases. Recommendations as educational examples were provided. Microanatomical location of melanoma metastases was 1 subcapsular, 2 parenchymal and 11 combined. The smallest and largest difference in measurements were 0.24 mm and 4.81 mm, respectively. 11/14 cases (78.6%) showed no agreement regarding the 1.0 mm cut-off. The median discrepancy for cases ≤5 deposits was 0.5 mm (range 0.24-0.60, n=3) and 2.51 mm (range 0.71-4.81, n=11) for cases with ≥6 deposits. Disconcordance in measuring SN tumour burden is correlated with the number of deposits. Awareness of this discordance in challenging cases, for example, cases with multiple small deposits, is important for clinical management. Illustrating cases to reduce differences in size measurement are provided.

RNA helicase DDX3 regulates RAD51 localization and DNA damage repair in Ewing sarcoma

We previously demonstrated that RNA helicase DDX3X (DDX3) can be a therapeutic target in Ewing sarcoma (EWS), but its role in EWS biology remains unclear. The present work demonstrates that DDX3 plays a unique role in DNA damage repair (DDR). We show that DDX3 interacts with several proteins involved in homologous recombination, including RAD51, RECQL1, RPA32, and XRCC2. In particular, DDX3 colocalizes with RAD51 and RNA:DNA hybrid structures in the cytoplasm of EWS cells. Inhibition of DDX3 RNA helicase activity increases cytoplasmic RNA:DNA hybrids, sequestering RAD51 in the cytoplasm, which impairs nuclear translocation of RAD51 to sites of double-stranded DNA breaks, thus increasing sensitivity of EWS to radiation treatment, both in vitro and in vivo. This discovery lays the foundation for exploring new therapeutic approaches directed at manipulating DDR protein localization in solid tumors.

Predicting Recurrence-Free and Overall Survival for Patients With Stage II Melanoma: The MIA Calculator

PURPOSE

Improvements in recurrence-free survival (RFS) were demonstrated in two recent randomized trials for patients with sentinel node (SN)-negative stage IIB or IIC melanoma receiving adjuvant systemic therapy (pembrolizumab/nivolumab). However, adverse events also occurred. Accurate individualized prognostic estimates of RFS and overall survival (OS) would allow patients to more accurately weigh the risks and benefits of adjuvant therapy. Since the current American Joint Committee on Cancer eighth edition (AJCC-8) melanoma staging system focuses on melanoma-specific survival, we developed a multivariable risk prediction calculator that provides estimates of 5- and 10-year RFS and OS for these patients.

METHODS

Data were extracted from the Melanoma Institute Australia (MIA) database for patients diagnosed with stage II (clinical or pathological) melanoma (n = 3,220). Survival prediction models were developed using multivariable Cox regression analyses (MIA models) and externally validated twice using data sets from the United States and the Netherlands. Each model's performance was assessed using C-statistics and calibration plots and compared with Cox models on the basis of AJCC-8 staging (stage models).

RESULTS

The 5-year and 10-year RFS C-statistics were 0.70 and 0.73 (MIA-model) versus 0.61 and 0.60 (stage-model), respectively. For OS, the 5-year and 10-year C-statistics were 0.71 and 0.75 (MIA-model) compared with 0.62 and 0.61 (stage-model), respectively. The MIA models were well calibrated and externally validated.

CONCLUSION

The MIA models offer accurate and personalized estimates of both RFS and OS in patients with stage II melanoma even in the absence of pathological staging with SN biopsy. These models were robust on external validations and may be used in everyday practice both with (ideally) and without performing SN biopsy to identify high-risk patients for further management strategies. An online tool will be available at the MIA website (Risk Prediction Tools).

The Diagnostic Value of microRNA Expression Analysis in Detecting Intraductal Papillomas in Patients with Pathological Nipple Discharge

Patients with pathological nipple discharge (PND) often undergo local surgical procedures because standard radiologic imaging fails to identify the underlying cause. MicroRNA (MiRNA) expression analysis of nipple fluid holds potential for distinguishing between breast diseases. This study aimed to compare miRNA expression levels between nipple fluids from patients with PND to identify possible relevant miRNAs that could differentiate between intraductal papillomas and no abnormalities in the breast tissue. Nipple fluid samples from patients with PND without radiological and pathological suspicion for malignancy who underwent a ductoscopy procedure were analyzed. We used univariate and multivariate regression analyses to identify nipple fluid miRNAs differing between pathologically confirmed papillomas and breast tissue without abnormalities. A total of 27 nipple fluid samples from patients with PND were included for miRNA expression analysis. Out of the 22 miRNAs examined, only miR-145-5p was significantly differentially expressed (upregulated) in nipple fluid from patients with an intraductal papilloma compared to patients showing no breast abnormalities (OR 4.76, p = 0.046), with a diagnostic accuracy of 92%. miR-145-5p expression in nipple fluid differs for intraductal papillomas and breast tissue without abnormalities and, therefore, has potential as a diagnostic marker to signal presence of papillomas in PND patients. However, further refinement and validation in clinical trials are necessary to establish its clinical applicability.

Long-term outcomes of young, node-negative, chemotherapy-naïve, triple-negative breast cancer patients according to BRCA1 status

BACKGROUND

Due to the abundant usage of chemotherapy in young triple-negative breast cancer (TNBC) patients, the unbiased prognostic value of BRCA1-related biomarkers in this population remains unclear. In addition, whether BRCA1-related biomarkers modify the well-established prognostic value of stromal tumor-infiltrating lymphocytes (sTILs) is unknown. This study aimed to compare the outcomes of young, node-negative, chemotherapy-naïve TNBC patients according to BRCA1 status, taking sTILs into account.

METHODS

We included 485 Dutch women diagnosed with node-negative TNBC under age 40 between 1989 and 2000. During this period, these women were considered low-risk and did not receive chemotherapy. BRCA1 status, including pathogenic germline BRCA1 mutation (gBRCA1m), somatic BRCA1 mutation (sBRCA1m), and tumor BRCA1 promoter methylation (BRCA1-PM), was assessed using DNA from formalin-fixed paraffin-embedded tissue. sTILs were assessed according to the international guideline. Patients' outcomes were compared using Cox regression and competing risk models.

RESULTS

Among the 399 patients with BRCA1 status, 26.3% had a gBRCA1m, 5.3% had a sBRCA1m, 36.6% had tumor BRCA1-PM, and 31.8% had BRCA1-non-altered tumors. Compared to BRCA1-non-alteration, gBRCA1m was associated with worse overall survival (OS) from the fourth year after diagnosis (adjusted HR, 2.11; 95% CI, 1.18-3.75), and this association attenuated after adjustment for second primary tumors. Every 10% sTIL increment was associated with 16% higher OS (adjusted HR, 0.84; 95% CI, 0.78-0.90) in gBRCA1m, sBRCA1m, or BRCA1-non-altered patients and 31% higher OS in tumor BRCA1-PM patients. Among the 66 patients with tumor BRCA1-PM and ≥ 50% sTILs, we observed excellent 15-year OS (97.0%; 95% CI, 92.9-100%). Conversely, among the 61 patients with gBRCA1m and < 50% sTILs, we observed poor 15-year OS (50.8%; 95% CI, 39.7-65.0%). Furthermore, gBRCA1m was associated with higher (adjusted subdistribution HR, 4.04; 95% CI, 2.29-7.13) and tumor BRCA1-PM with lower (adjusted subdistribution HR, 0.42; 95% CI, 0.19-0.95) incidence of second primary tumors, compared to BRCA1-non-alteration.

CONCLUSIONS

Although both gBRCA1m and tumor BRCA1-PM alter BRCA1 gene transcription, they are associated with different outcomes in young, node-negative, chemotherapy-naïve TNBC patients. By combining sTILs and BRCA1 status for risk classification, we were able to identify potential subgroups in this population to intensify and optimize adjuvant treatment.

Erratum: Acute cellular and vascular responses to photodynamic therapy using EGFR-targeted nanobody-photosensitizer conjugates studied with intravital optical imaging and magnetic resonance imaging: Erratum

[This corrects the article DOI: 10.7150/thno.37949.].

Proteomics on malignant pleural effusions reveals ERα loss in metastatic breast cancer associates with SGK1-NDRG1 deregulation

Breast cancer (BCa) is a highly heterogeneous disease, with hormone receptor status being a key factor in patient prognostication and treatment decision-making. The majority of primary tumours are positive for oestrogen receptor alpha (ERα), which plays a key role in tumorigenesis and disease progression, and represents the major target for treatment of BCa. However, around one-third of patients with ERα-positive BCa relapse and progress into the metastatic stage, with 20% of metastatic cases characterised by loss of ERα expression after endocrine treatment, known as ERα-conversion. It remains unclear whether ERα-converted cancers are biologically similar to bona fide ERα-negative disease and which signalling cascades compensate for ERα loss and drive tumour progression. To better understand the biological changes that occur in metastatic BCa upon ERα loss, we performed (phospho)proteomics analysis of 47 malignant pleural effusions derived from 37 BCa patients, comparing ERα-positive, ERα-converted and ERα-negative cases. Our data revealed that the loss of ERα-dependency in this metastatic site leads to only a partial switch to an ERα-negative molecular phenotype, with preservation of a luminal-like proteomic landscape. Furthermore, we found evidence for decreased activity of several key kinases, including serum/glucocorticoid regulated kinase 1 (SGK1), in ERα-converted metastases. Loss of SGK1 substrate phosphorylation may compensate for the loss of ERα-dependency in advanced disease and exposes a potential therapeutic vulnerability that may be exploited in treating these patients.

Use of the ISUP e-learning module improves interrater reliability in prostate cancer grading

AIMS

Prostate cancer (PCa) grading is an important prognostic parameter, but is subject to considerable observer variation. Previous studies have shown that interobserver variability decreases after participants were trained using an e-learning module. However, since the publication of these studies, grading of PCa has been enhanced by adopting the International Society of Urological Pathology (ISUP) 2014 grading classification. This study investigates the effect of training on interobserver variability of PCa grading, using the ISUP Education web e-learning on Gleason grading.

METHODS

The ISUP Education Prostate Test B Module was distributed among Dutch pathologists. The module uses images graded by the ISUP consensus panel consisting of 24 expert uropathologists. Participants graded the same 10 images before and after e-learning. We included those who completed the tests before and after training. We evaluated variation in PCa grading in a fully crossed study design, using linearly weighted kappa values for each pathologist, comparing them to other pathologists and to the ISUP consensus panel. We analysed the improvement in median weighted kappas before and after training, using Wilcoxon's signed rank-test.

RESULTS

We included 42 pathologists. Inter-rater reliability between pathologists improved from 0.70 before training to 0.74 after training (p=0.01). When compared with the ISUP consensus panel, five pathologists improved significantly, whereas the kappa of one pathologist was significantly lower after training. All pathologists who improved significantly, graded with less than substantial agreement before training.

CONCLUSIONS

ISUP Prostate Test B e-learning reduces variability in PCa grading. E-learning is a cost-effective method for standardisation of pathology.

A tumor cell specific Zona Pellucida glycoprotein 3 RNA transcript encodes an intracellular cancer antigen

Background

Expression of Zona Pellucida glycoprotein 3 (ZP3) in healthy tissue is restricted to the extracellular Zona Pellucida layer surrounding oocytes of ovarian follicles and to specific cells of the spermatogenic lineage. Ectopic expression of ZP3 has been observed in various types of cancer, rendering it a possible therapeutic target.

Methods

To support its validity as therapeutic target, we extended the cancer related data by investigating ZP3 expression using immunohistochemistry (IHC) of tumor biopsies. We performed a ZP3 transcript specific analysis of publicly available RNA-sequencing (RNA-seq) data of cancer cell lines (CCLs) and tumor and normal tissues, and validated expression data by independent computational analysis and real-time quantitative PCR (qPCR). A correlation between the ZP3 expression level and pathological and clinical parameters was also investigated.

Results

IHC data for several cancer types showed abundant ZP3 protein staining, which was confined to the cytoplasm, contradicting the extracellular protein localization in oocytes. We noticed that an alternative ZP3 RNA transcript, which we term 'ZP3-Cancer', was annotated in gene databases that lacks the genetic information encoding the N-terminal signal peptide that governs entry into the secretory pathway. This explains the intracellular localization of ZP3 in tumor cells. Analysis of publicly available RNA-seq data of 1339 cancer cell lines (CCLs), 10386 tumor tissues (The Cancer Genome Atlas) and 7481 healthy tissues (Genotype-Tissue Expression) indicated that ZP3-Cancer is the dominant ZP3 RNA transcript in tumor cells and is highly enriched in many cancer types, particularly in rectal, ovarian, colorectal, prostate, lung and breast cancer. Expression of ZP3-Cancer in tumor cells was confirmed by qPCR. Higher levels of the ZP3-Cancer transcript were associated with more aggressive tumors and worse survival of patients with various types of cancer.

Conclusion

The cancer-restricted expression of ZP3-Cancer renders it an attractive tumor antigen for the development of a therapeutic cancer vaccine, particularly using mRNA expression technologies.

External validation and clinical utility assessment of PREDICT breast cancer prognostic model in young, systemic treatment-naïve women with node-negative breast cancer

BACKGROUND

The validity of the PREDICT breast cancer prognostic model is unclear for young patients without adjuvant systemic treatment. This study aimed to validate PREDICT and assess its clinical utility in young women with node-negative breast cancer who did not receive systemic treatment.

METHODS

We selected all women from the Netherlands Cancer Registry who were diagnosed with node-negative breast cancer under age 40 between 1989 and 2000, a period when adjuvant systemic treatment was not standard practice for women with node-negative disease. We evaluated the calibration and discrimination of PREDICT using the observed/expected (O/E) mortality ratio, and the area under the receiver operating characteristic curve (AUC), respectively. Additionally, we compared the potential clinical utility of PREDICT for selectively administering chemotherapy to the chemotherapy-to-all strategy using decision curve analysis at predefined thresholds.

RESULTS

A total of 2264 women with a median age at diagnosis of 36 years were included. Of them, 71.2% had estrogen receptor (ER)-positive tumors and 44.0% had grade 3 tumors. Median tumor size was 16 mm. PREDICT v2.2 underestimated 10-year all-cause mortality by 33% in all women (O/E ratio:1.33, 95%CI:1.22-1.43). Model discrimination was moderate overall (AUC10-year:0.65, 95%CI:0.62-0.68), and poor for women with ER-negative tumors (AUC10-year:0.56, 95%CI:0.51-0.62). Compared to the chemotherapy-to-all strategy, PREDICT only showed a slightly higher net benefit in women with ER-positive tumors, but not in women with ER-negative tumors.

CONCLUSIONS

PREDICT yields unreliable predictions for young women with node-negative breast cancer. Further model updates are needed before PREDICT can be routinely used in this patient subset.

Deep Learning-Based Segmentation of Locally Advanced Breast Cancer on MRI in Relation to Residual Cancer Burden: A Multi-Institutional Cohort Study

BACKGROUND

While several methods have been proposed for automated assessment of breast-cancer response to neoadjuvant chemotherapy on breast MRI, limited information is available about their performance across multiple institutions.

PURPOSE

To assess the value and robustness of deep learning-derived volumes of locally advanced breast cancer (LABC) on MRI to infer the presence of residual disease after neoadjuvant chemotherapy.

STUDY TYPE

Retrospective.

SUBJECTS

Training cohort: 102 consecutive female patients with LABC scheduled for neoadjuvant chemotherapy (NAC) from a single institution (age: 25-73 years). Independent testing cohort: 55 consecutive female patients with LABC from four institutions (age: 25-72 years).

FIELD STRENGTH/SEQUENCE

Training cohort: single vendor 1.5 T or 3.0 T. Testing cohort: multivendor 3.0 T. Gradient echo dynamic contrast-enhanced sequences.

ASSESSMENT

A convolutional neural network (nnU-Net) was trained to segment LABC. Based on resulting tumor volumes, an extremely randomized tree model was trained to assess residual cancer burden (RCB)-0/I vs. RCB-II/III. An independent model was developed using functional tumor volume (FTV). Models were tested on an independent testing cohort and response assessment performance and robustness across multiple institutions were assessed.

STATISTICAL TESTS

The receiver operating characteristic (ROC) was used to calculate the area under the ROC curve (AUC). DeLong's method was used to compare AUCs. Correlations were calculated using Pearson's method. P values <0.05 were considered significant.

RESULTS

Automated segmentation resulted in a median (interquartile range [IQR]) Dice score of 0.87 (0.62-0.93), with similar volumetric measurements (R = 0.95, P < 0.05). Automated volumetric measurements were significantly correlated with FTV (R = 0.80). Tumor volume-derived from deep learning of DCE-MRI was associated with RCB, yielding an AUC of 0.76 to discriminate between RCB-0/I and RCB-II/III, performing similar to the FTV-based model (AUC = 0.77, P = 0.66). Performance was comparable across institutions (IQR AUC: 0.71-0.84).

DATA CONCLUSION

Deep learning-based segmentation estimates changes in tumor load on DCE-MRI that are associated with RCB after NAC and is robust against variations between institutions.

EVIDENCE LEVEL

2.

TECHNICAL EFFICACY

Stage 4.

MET-receptor targeted fluorescent imaging and spectroscopy to detect multifocal papillary thyroid cancer

PURPOSE

Multifocal disease in PTC is associated with an increased recurrence rate. Multifocal disease (MD) is underdiagnosed with the current gold standard of pre-operative ultrasound staging. Here, we evaluate the use of EMI-137 targeted molecular fluorescence-guided imaging (MFGI) and spectroscopy as a tool for the intra-operative detection of uni- and multifocal papillary thyroid cancer (PTC) aiming to improve disease staging and treatment selection.

METHODS

A phase-1 study (NCT03470259) with EMI-137 was conducted to evaluate the possibility of detecting PTC using MFGI and quantitative fiber-optic spectroscopy.

RESULTS

Fourteen patients underwent hemi- or total thyroidectomy (TTX) after administration of 0.09 mg/kg (n = 1), 0.13 mg/kg (n = 8), or 0.18 mg/kg (n = 5) EMI-137. Both MFGI and spectroscopy could differentiate PTC from healthy thyroid tissue after administration of EMI-137, which binds selectively to MET in PTC. 0.13 mg/kg was the lowest dosage EMI-137 that allowed for differentiation between PTC and healthy thyroid tissue. The smallest PTC focus detected by MFGI was 1.4 mm. MFGI restaged 80% of patients from unifocal to multifocal PTC compared to ultrasound.

CONCLUSION

EMI-137-guided MFGI and spectroscopy can be used to detect multifocal PTC. This may improve disease staging and treatment selection between hemi- and total thyroidectomy by better differentiation between unifocal and multifocal disease.

TRIAL REGISTRATION

NCT03470259.

[Breast cancer during pregnancy and the postpartum period: challenging diagnosis of an aggressive disease]

Breast cancer is the most common malignancy diagnosed during pregnancy. Breast cancer during pregnancy or within the first postpartum year is commonly described as Pregnancy-Associated Breast Cancer (PABC). PABC often exhibits poorer histopathologic features and has a worse prognosis when compared to young breast cancer patients without a current or recent pregnancy. Here, we describe two cases of PABC in which the presenting symptoms of the patients were interpreted as pregnancy-related changes, causing a diagnostic delay. Therefore, we argue that every pregnant or postpartum woman with changes in the breast must be thoroughly evaluated to exclude the possibility of a malignancy. In case of any suspicion, patients must be referred to a breast cancer center for further evaluation.

Interlaboratory Gleason grading variation affects treatment: a Dutch historic cohort study in 30 509 patients with prostate cancer

AIM

Substantial variation in Gleason grading (GG) of prostate cancer (PCa) exists between Dutch pathology laboratories. This study investigates its impact on treatment strategies.

METHODS

Pathology reports of prostate needle biopsies and clinical data of patients with PCa diagnosed between 2017 and 2019 were retrieved from the Dutch nationwide network and registry of histopathology and cytopathology and The Netherlands Cancer Registry. We investigated the impact of grading variation on treatment strategy for patients whose grade was decisive in treatment choice. First, we evaluated the effect of grading practice (low, average or high grading) on active treatment (AT) versus active surveillance in patients with prostate-specific antigen (PSA) <10 ng/mL and cT1c/cT2a disease. Second, we assessed the association of grading practice with performance of pelvic lymph node dissection (PLND) in patients with PSA 10-20 ng/mL or cT2b disease. We used multivariable logistic regression to analyse the relation between laboratories' grading practices and AT or PLND.

RESULTS

We included 30 509 patients. GG was decisive in treatment strategy for 11 925 patients (39%). AT was performed significantly less often in patients diagnosed by laboratories that graded lower than average (OR=0.77, 95% CI 0.68 to 0.88). Conversely, patients received AT significantly more often when diagnosed in high-grading laboratories versus average-grading laboratories (OR=1.21, 95% CI 1.03 to1.43). PLND was performed significantly less often in patients diagnosed by low-grading versus average-grading laboratories (OR=0.66, 95% CI 0.48 to 0.90).

CONCLUSION

Our study shows that the odds that a patient undergoes AT or PLND, depends on laboratories' grading practices in a substantial number of patients. This likely influences patient prognosis and outcome, necessitating standardisation of GG to prevent suboptimal patient outcome.

A Second Ductoscopy Procedure in Patients with Recurrent and Persistent Pathological Nipple Discharge

Background

Most patients suffering from pathological nipple discharge (PND) undergo local surgical procedures because standard radiological imaging often fails to reveal the cause. Ductoscopy is a minimally invasive endoscopic technique that enables direct intraductal visualization and can avoid unnecessary diagnostic surgical procedures. Hence, patients with recurrent or persistent PND after an unsuccessful ductoscopy procedure still undergo unnecessary surgery. This study describes the experience of a second ductoscopy procedure in patients with recurrent or persistent PND without suspicious radiological findings.

Methods

Patients with recurrent or persistent PND who underwent two ductoscopy procedures between 2010 and 2017 were retrospectively analyzed. The second ductoscopy was performed when the first ductoscopic attempt was unsuccessful due to technical problems. The primary outcome was the number of preventable surgical procedures.

Results

A total of 17 patients underwent two ductoscopy procedures. The first ductoscopy showed a polypoid lesion in 10 patients (58.8%), no abnormalities in 3 patients (17.6%), and in 4 patients (23.5%), it was not possible to visualize the ductal tree. Post-procedure, all patients suffered from PND. After two ductoscopic attempts, PND stopped in 10 patients (58.8%), and 7 patients (41.2%) still suffered from PND and were operated on. Pathology of the resection specimens showed no abnormalities in 1 patient, a papilloma in 5 patients, and ductal carcinoma in situ in 1 patient.

Conclusion

A second ductoscopy procedure can be considered in the diagnostic work-up of patients suffering from persistent or recurrent PND after an unsuccessful first ductoscopic attempt to avoid unnecessary surgery in about 59% of the cases.

Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

A comprehensive multi-domain dataset for mitotic figure detection

The prognostic value of mitotic figures in tumor tissue is well-established for many tumor types and automating this task is of high research interest. However, especially deep learning-based methods face performance deterioration in the presence of domain shifts, which may arise from different tumor types, slide preparation and digitization devices. We introduce the MIDOG++ dataset, an extension of the MIDOG 2021 and 2022 challenge datasets. We provide region of interest images from 503 histological specimens of seven different tumor types with variable morphology with in total labels for 11,937 mitotic figures: breast carcinoma, lung carcinoma, lymphosarcoma, neuroendocrine tumor, cutaneous mast cell tumor, cutaneous melanoma, and (sub)cutaneous soft tissue sarcoma. The specimens were processed in several laboratories utilizing diverse scanners. We evaluated the extent of the domain shift by using state-of-the-art approaches, observing notable differences in single-domain training. In a leave-one-domain-out setting, generalizability improved considerably. This mitotic figure dataset is the first that incorporates a wide domain shift based on different tumor types, laboratories, whole slide image scanners, and species.

Role of duct excision surgery in the treatment of pathological nipple discharge and detection of breast carcinoma: systematic review

BACKGROUND

The role of duct excision surgery is not clearly defined in patients with pathological nipple discharge without other clinical and radiological abnormalities. The primary aim of this systematic review was to determine the malignancy rate in patients with pathological nipple discharge after duct excision surgery (microdochectomy/major duct excision). The secondary aims were to determine the recurrence rate of pathological nipple discharge after surgery and to assess breast cancer development after surgery.

METHODS

MEDLINE and Embase were searched from inception to March 2023, using search terms related to 'nipple discharge', 'nipple fluid', 'microdochectomy', 'duct excision', and 'minimally invasive surgical procedure'. Studies reporting data about women who underwent duct excision surgery for pathological nipple discharge without clinical and radiological suspicion of breast cancer, as well as reporting data on women diagnosed with breast cancer after duct excision surgery, were included.

RESULTS

A total of 318 titles were identified, of which nine publications were included in the analysis. This resulted in 1108 patients with pathological nipple discharge who underwent a duct excision. The weighted mean rate of malignancy after duct excision surgery was 8.1 per cent (ranging from 2.3 to 13.5 per cent). Three studies described the recurrence rate of pathological nipple discharge (ranging from 0 to 12 per cent) and two studies reported breast cancer development in the follow-up in a total of three patients (less than 1 per cent).

CONCLUSION

The malignancy rate after duct excision surgery for pathological nipple discharge was low in patients with pathological nipple discharge without radiological and clinical abnormalities and approximately 9 of 10 patients undergo surgery for a benign cause. Improvement of the diagnostic and therapeutic workup is needed to prevent patients from undergoing (unnecessary) exploratory surgery.

R-spondin-3 promotes proliferation and invasion of breast cancer cells independently of Wnt signaling

We recently identified R-spondin-3 (RSPO3) as a novel driver of breast cancer associating with reduced patient survival, expanding its clinical value as potential therapeutic target that had been recognized mostly for colorectal cancer so far. (Pre)clinical studies exploring RSPO3 targeting in colorectal cancer approach this indirectly with Wnt inhibitors, or directly with anti-RSPO3 antibodies. Here, we address the clinical relevance of RSPO3 in breast cancer and provide insight in the oncogenic activities of RSPO3. Utilizing the RSPO3 breast cancer mouse model, we show that RSPO3 drives the aberrant expansion of luminal progenitor cells expressing cancer stem cell marker CD61, inducing proliferative, poorly differentiated and invasive tumors. Complementary studies with tumor organoids and human breast cancer cell lines demonstrate that RSPO3 consistently promotes the proliferation and invasion of breast cancer cells. Importantly, RSPO3 exerts these oncogenic effects independently of Wnt signaling, rejecting the therapeutic value of Wnt inhibitors in RSPO3-driven breast cancer. Instead, direct RSPO3 targeting effectively inhibited RSPO3-driven growth of breast cancer cells. Conclusively, our data indicate that RSPO3 exerts unfavorable oncogenic effects in breast cancer, enhancing proliferation and malignancy in a Wnt-independent fashion, proposing RSPO3 itself as a valuable therapeutic target in breast cancer.

Third International Consensus Conference on lesions of uncertain malignant potential in the breast (B3 lesions)

The heterogeneous group of B3 lesions in the breast harbors lesions with different malignant potential and progression risk. As several studies about B3 lesions have been published since the last Consensus in 2018, the 3rd International Consensus Conference discussed the six most relevant B3 lesions (atypical ductal hyperplasia (ADH), flat epithelial atypia (FEA), classical lobular neoplasia (LN), radial scar (RS), papillary lesions (PL) without atypia, and phyllodes tumors (PT)) and made recommendations for diagnostic and therapeutic approaches. Following a presentation of current data of each B3 lesion, the international and interdisciplinary panel of 33 specialists and key opinion leaders voted on the recommendations for further management after core-needle biopsy (CNB) and vacuum-assisted biopsy (VAB). In case of B3 lesion diagnosis on CNB, OE was recommended in ADH and PT, whereas in the other B3 lesions, vacuum-assisted excision was considered an equivalent alternative to OE. In ADH, most panelists (76%) recommended an open excision (OE) after diagnosis on VAB, whereas observation after a complete VAB-removal on imaging was accepted by 34%. In LN, the majority of the panel (90%) preferred observation following complete VAB-removal. Results were similar in RS (82%), PL (100%), and FEA (100%). In benign PT, a slim majority (55%) also recommended an observation after a complete VAB-removal. VAB with subsequent active surveillance can replace an open surgical intervention for most B3 lesions (RS, FEA, PL, PT, and LN). Compared to previous recommendations, there is an increasing trend to a de-escalating strategy in classical LN. Due to the higher risk of upgrade into malignancy, OE remains the preferred approach after the diagnosis of ADH.

RNA Helicase DDX3 Regulates RAD51 Localization and DNA Damage Repair in Ewing Sarcoma

We previously demonstrated that RNA helicase DDX3X (DDX3) can be a therapeutic target in Ewing sarcoma (EWS), but its role in EWS biology remains unclear. The present work demonstrates that DDX3 plays a unique role in DNA damage repair (DDR). We show that DDX3 interacts with several proteins involved in homologous recombination, including RAD51, RECQL1, RPA32, and XRCC2. In particular, DDX3 colocalizes with RAD51 and RNA:DNA hybrid structures in the cytoplasm of EWS cells. Inhibition of DDX3 RNA helicase activity increases cytoplasmic RNA:DNA hybrids, sequestering RAD51 in the cytoplasm, which impairs nuclear translocation of RAD51 to sites of double-stranded DNA breaks thus increasing sensitivity of EWS to radiation treatment, both in vitro and in vivo. This discovery lays the foundation for exploring new therapeutic approaches directed at manipulating DDR protein localization in solid tumors.

CONFIDENT-trial protocol: a pragmatic template for clinical implementation of artificial intelligence assistance in pathology

INTRODUCTION

Artificial intelligence (AI) has been on the rise in the field of pathology. Despite promising results in retrospective studies, and several CE-IVD certified algorithms on the market, prospective clinical implementation studies of AI have yet to be performed, to the best of our knowledge. In this trial, we will explore the benefits of an AI-assisted pathology workflow, while maintaining diagnostic safety standards.

METHODS AND ANALYSIS

This is a Standard Protocol Items: Recommendations for Interventional Trials-Artificial Intelligence compliant single-centre, controlled clinical trial, in a fully digital academic pathology laboratory. We will prospectively include prostate cancer patients who undergo prostate needle biopsies (CONFIDENT-P) and breast cancer patients who undergo a sentinel node procedure (CONFIDENT-B) in the University Medical Centre Utrecht. For both the CONFIDENT-B and CONFIDENT-P trials, the specific pathology specimens will be pseudo-randomised to be assessed by a pathologist with or without AI assistance in a pragmatic (bi-)weekly sequential design. In the intervention group, pathologists will assess whole slide images (WSI) of the standard hematoxylin and eosin (H&E)-stained sections assisted by the output of the algorithm. In the control group, pathologists will assess H&E WSI according to the current clinical workflow. If no tumour cells are identified or when the pathologist is in doubt, immunohistochemistry (IHC) staining will be performed. At least 80 patients in the CONFIDENT-P and 180 patients in the CONFIDENT-B trial will need to be enrolled to detect superiority, allocated as 1:1. Primary endpoint for both trials is the number of saved resources of IHC staining procedures for detecting tumour cells, since this will clarify tangible cost savings that will support the business case for AI.

ETHICS AND DISSEMINATION

The ethics committee (MREC NedMec) waived the need of official ethical approval, since participants are not subjected to procedures nor are they required to follow rules. Results of both trials (CONFIDENT-B and CONFIDENT-P) will be published in scientific peer-reviewed journals.

Time Trends in Histopathological Findings in Mammaplasty Specimens in a Dutch Academic Pathology Laboratory

Reduction mammaplasties are often performed at a relatively young age. Necessity of routine pathological investigation of the removed breast tissue to exclude breast cancer has been debated. Past studies have shown 0.05%-4.5% significant findings in reduction specimens, leading to an ongoing debate whether this is cost-effective. There is also no current Dutch guideline on pathological investigation of mammaplasty specimens. Because the incidence of breast cancer is rising, especially among young women, we re-evaluated the yield of routine pathological investigation of mammaplasty specimens over three decades in search of time trends.

Methods

Reduction specimens from 3430 female patients examined from 1988 to 2021 in the UMC Utrecht were evaluated. Significant findings were defined as those that may lead to more intensive follow-up or surgical intervention.

Results

Mean age of patients was 39 years. Of the specimens, 67.4% were normal; 28.9% displayed benign changes; 2.7%, benign tumors; 0.3%, premalignant changes; 0.8%, in situ; and 0.1%, invasive cancers. Most patients with significant findings were in their forties (P < 0.001), the youngest patient being 29 years. Significant findings increased from 2016 onward (P = 0.0001), 86.8% found after 2016.

Conclusions

Over three decades, 1.2% of mammaplasty specimens displayed significant findings on routine pathology examination, with an incidence rising to 2.1% from 2016 onward. The main reason for this recent increase is probably attributable to super-specialization by the pathologists. While awaiting formal cost-effectiveness studies, the frequency of significant findings for now seems to justify routine pathological examination of mammaplasty reduction specimens.

Deep learning supported mitoses counting on whole slide images: A pilot study for validating breast cancer grading in the clinical workflow

Introduction

Breast cancer (BC) prognosis is largely influenced by histopathological grade, assessed according to the Nottingham modification of Bloom-Richardson (BR). Mitotic count (MC) is a component of histopathological grading but is prone to subjectivity. This study investigated whether mitoses counting in BC using digital whole slide images (WSI) compares better to light microscopy (LM) when assisted by artificial intelligence (AI), and to which extent differences in digital MC (AI assisted or not) result in BR grade variations.

Methods

Fifty BC patients with paired core biopsies and resections were randomly selected. Component scores for BR grade were extracted from pathology reports. MC was assessed using LM, WSI, and AI. Different modalities (LM-MC, WSI-MC, and AI-MC) were analyzed for correlation with scatterplots and linear regression, and for agreement in final BR with Cohen's κ.

Results

MC modalities strongly correlated in both biopsies and resections: LM-MC and WSI-MC (R² 0.85 and 0.83, respectively), LM-MC and AI-MC (R² 0.85 and 0.95), and WSI-MC and AI-MC (R² 0.77 and 0.83). Agreement in BR between modalities was high in both biopsies and resections: LM-MC and WSI-MC (κ 0.93 and 0.83, respectively), LM-MC and AI-MC (κ 0.89 and 0.83), and WSI-MC and AI-MC (κ 0.96 and 0.73).

Conclusion

This first validation study shows that WSI-MC may compare better to LM-MC when using AI. Agreement between BR grade based on the different mitoses counting modalities was high. These results suggest that mitoses counting on WSI can well be done, and validate the presented AI algorithm for pathologist supervised use in daily practice. Further research is required to advance our knowledge of AI-MC, but it appears at least non-inferior to LM-MC.

Papillomatous breast lesions with atypical columnar cell features

AIMS

Columnar cell lesions (CCLs) are recognised breast cancer precursor lesions. Intraductal papillomas are usually lined by benign (polyclonal) cells. Although papillomas with monoclonal lesions (atypical ductal hyperplasia (ADH)/ductal carcinoma in situ (DCIS)) have been described, CCLs have not been described in papillomas.

METHODS

We present two papillary breast lesions lined by a single layer of luminal cells resembling atypical CCL/flat epithelial atypia (FEA). We compared these two lesions with 13 benign intraductal papillomas, and 2 papillomas with ADH/DCIS grade 1 features as controls were immunohistochemically stained for the oestrogen receptor alpha (oestrogen receptor) and progesterone receptors (PR), cytokeratin 5 (CK5) and cyclin D1.

RESULTS

Oestrogen receptor/PR expression was variable, with areas with ≥85% hormone receptor positivity in both morphologically normal papillomas and papillomas with ADH. In ADH areas, CK5 expression was seen in ≤5% of cells while cyclin D1 expression was high (>60%). The two papillary lesions with FEA were 100% oestrogen receptor and 90% cyclin D1 positive, and low on PR/CK5. There was only one morphologically normal papilloma with similar areas of low CK5 (5%) and high cyclin D1 expression; in all other morphologically benign papillomas CK5 expression varied between 10% and 50% and cyclin D1 expression was ≤50%. The papillary lesion with FEA that could be tested showed 16q losses, the hallmark genetic change in low nuclear grade breast neoplasias, in contrast to nine morphologically benign papillomas that could be tested.

CONCLUSION

We present two papillomatous breast lesions with atypical CCL morphology and 16q loss, for which we propose the term papillary FEA.

Melanomas in children and adolescents: Clinicopathologic features and survival outcomes

BACKGROUND

Melanomas in the first 2 decades of life are uncommon and poorly understood.

OBJECTIVE

To assess clinicopathologic features and survival of children (≤11 years) and adolescents (12-19 years) diagnosed with melanoma.

METHODS

A pooled cohort of 514 patients was analyzed (397 Dutch, 117 Australian; 62 children, 452 adolescents). Pathology reports were reevaluated to determine melanoma subtypes. Multivariable Cox models were generated for recurrence-free survival (RFS) and overall survival (OS).

RESULTS

Melanoma subtypes were conventional melanoma (superficial spreading, nodular, desmoplastic, and acral lentiginous), spitzoid melanoma, and melanoma associated with a congenital nevus in 428, 78, and 8 patients, respectively. Ten-year RFS was 91.5% (95% confidence interval [CI], 82.4%-100%) in children and 86.4% (95% CI, 82.7%-90.3%) in adolescents (P = .32). Ten-year OS was 100% in children and 92.7% (95% CI, 89.8%-95.8%) in adolescents (P = .09). On multivariable analysis possible only for the adolescent cohort due to the small number of children, ulceration status, and anatomic site were associated with RFS and OS, whereas age, sex, mitotic index, sentinel node status and melanoma subtype were not. Breslow thickness >4 mm was associated with worse RFS.

LIMITATIONS

Retrospective study.

CONCLUSIONS

Survival rates for children and adolescents with melanomas were high. Ulceration, head or neck location and Breslow thickness >4 mm predicted worse survival in adolescents.

A whole-slide imaging based workflow reduces the reading time of pathologists

Even though entirely digitized microscopic tissue sections (whole slide images, WSIs) are increasingly being used in histopathology diagnostics, little data is still available on the effect of this technique on pathologists' reading time. This study aimed to compare the time required to perform the microscopic assessment by pathologists between a conventional workflow (an optical microscope) and digitized WSIs. WSI was used in primary diagnostics at the Laboratory for Pathology Eastern Netherlands for several years (LabPON, Hengelo, The Netherlands). Cases were read either in a traditional workflow, with the pathologist recording the time required for diagnostics and reporting, or entirely digitally. Reading times were extracted from image management system log files, and the digitized workflow was fully integrated into the laboratory information system. The digital workflow saved time in the majority of case categories, with prostate biopsies saving the most (68% time gain). Taking into account case distribution, the digital workflow produced an average gain of 12.3%. Using WSI instead of conventional microscopy significantly reduces pathologists' reading times. Pathologists must work in a fully integrated environment to fully reap the benefits of a digital workflow.

Time interval from primary melanoma to first distant recurrence in relation to patient outcomes in advanced melanoma

Since the introduction of BRAF(/MEK) inhibition and immune checkpoint inhibition (ICI), the prognosis of advanced melanoma has greatly improved. Melanoma is known for its remarkably long time to first distant recurrence (TFDR), which can be decades in some patients and is partly attributed to immune-surveillance. We investigated the relationship between TFDR and patient outcomes after systemic treatment for advanced melanoma. We selected patients undergoing first-line systemic therapy for advanced melanoma from the nationwide Dutch Melanoma Treatment Registry. The association between TFDR and progression-free survival (PFS) and overall survival (OS) was assessed by Cox proportional hazard regression models. The TFDR was modeled categorically, linearly, and flexibly using restricted cubic splines. Patients received anti-PD-1-based treatment (n = 1844) or BRAF(/MEK) inhibition (n = 1618). For ICI-treated patients with a TFDR <2 years, median OS was 25.0 months, compared to 37.3 months for a TFDR >5 years (P = .014). Patients treated with BRAF(/MEK) inhibition with a longer TFDR also had a significantly longer median OS (8.6 months for TFDR <2 years compared to 11.1 months for >5 years, P = .004). The hazard of dying rapidly decreased with increasing TFDR until approximately 5 years (HR 0.87), after which the hazard of dying further decreased with increasing TFDR, but less strongly (HR 0.82 for a TFDR of 10 years and HR 0.79 for a TFDR of 15 years). Results were similar when stratifying for type of treatment. Advanced melanoma patients with longer TFDR have a prolonged PFS and OS, irrespective of being treated with first-line ICI or targeted therapy.

The CONFIDENT-P trial: Clinical implementation of artificial intelligence assistance in prostate cancer pathology

TPS405

Background: Prostate cancer grading has been subject to variation, putting patients at risk for over- and under-treatment (Flach et al., 2022). As a response, development of artificial intelligence (AI) prostate cancer algorithms has been on the rise in the field of pathology. Despite promising results in retrospective studies, and several FDA-approved and CE-IVD certified algorithms on the market, prospective clinical implementation studies of AI are lacking. Moreover, uptake of digital pathology is currently insufficient due to high implementation costs (Ho et al., 2014). In this trial, we will explore the benefits of an AI-assisted pathology workflow in prostate cancer detection, while maintaining diagnostic safety standards. We will focus on reducing costly immunohistochemistry stains (IHC), which are currently used to aid in the diagnosis of prostate cancer. Methods: CONFIDENT-P is a SPIRIT-AI compliant single-centre, clinical trial, in a fully digital academic pathology laboratory. We will prospectively enroll 80 prostate cancer patients who undergo prostate needle biopsies. The pathology specimens will be pseudo-randomized to be assessed by a pathologist with- or without AI-assistance in a pragmatic (bi-)weekly sequential design, in a 1:1 allocation ratio. Patients are excluded when they are redirected for a second opinion to the UMC Utrecht. In the intervention group, pathologists will assess whole slide images (WSI) of the standard haematoxylin-eosin (HE)-stained sections assisted by the output of a CE-IVD approved prostate cancer detection and grading algorithm. In the control group, pathologists will assess HE WSI according to the current clinical workflow. If no tumour cells are identified or when the pathologist is in doubt, staining by immunohistochemistry (IHC) will be performed. Primary endpoint is the number of saved resources on IHC for detecting tumour cells, since this will clarify tangible cost savings that will help to build the business case for AI. We will compare the proportion of IHC-use in both arms, and calculate adjusted relative risks, using a log-binomial model. The sample size gives at least 80% power to detect a 30% difference in IHC usage, using a one-sided significance level of 5%. Enrolment is set to begin in November 2022. The ethics committee (MREC NedMec) waived the need of official ethical approval, as participants are not subjected to procedures and as they are not required to follow rules. Furthermore, they are not at risk of an inferior diagnosis. Trial registration is therefore applicable nor suitable.

Plain Language Summary - Development and validation of risk calculators for people with "thin" melanomas on their skin to predict the likelihood that their cancer will return

WHAT IS THIS SUMMARY ABOUT?

This is a summary of an article describing the development of risk calculators for use in people who develop a type of melanoma on their skin called "thin" melanoma to predict the likelihood that their cancer will return. The article was originally published in the Journal of Clinical Oncology in 2021.

HOW WERE THE CALCULATORS DEVELOPED?

Calculations were performed to predict the chance of people with thin melanomas surviving without their melanoma recurring. Three graphical prediction calculators (called nomograms) were developed, along with easy-to-use online calculators using the same underlying calculation methods. The model was developed using data for 25,930 Dutch people diagnosed with thin melanomas (called the "development set"). To test its ability to predict melanoma recurrence, it was then compared with data for 2,968 Australian people with melanoma (the "validation set"). The calculators developed in the Dutch patients were found to accurately predict the risk of melanoma recurring for people with melanoma in the Australian "validation" group.

WHAT DO THE RESULTS MEAN?

The calculators provide estimates of the risk of the melanoma returning for people with thin melanomas. The easy-to-use online calculators are freely available on a smartphone, tablet or computer, and will assist in providing accurate estimates of recurrence risks for individuals with thin melanomas, allowing more intensive follow-up of those whose predicted risk of their melanoma returning is high.

CT radiomics compared to a clinical model for predicting checkpoint inhibitor treatment outcomes in patients with advanced melanoma

INTRODUCTION

Predicting checkpoint inhibitors treatment outcomes in melanoma is a relevant task, due to the unpredictable and potentially fatal toxicity and high costs for society. However, accurate biomarkers for treatment outcomes are lacking. Radiomics are a technique to quantitatively capture tumour characteristics on readily available computed tomography (CT) imaging. The purpose of this study was to investigate the added value of radiomics for predicting clinical benefit from checkpoint inhibitors in melanoma in a large, multicenter cohort.

METHODS

Patients who received first-line anti-PD1±anti-CTLA4 treatment for advanced cutaneous melanoma were retrospectively identified from nine participating hospitals. For every patient, up to five representative lesions were segmented on baseline CT, and radiomics features were extracted. A machine learning pipeline was trained on the radiomics features to predict clinical benefit, defined as stable disease for more than 6 months or response per RECIST 1.1 criteria. This approach was evaluated using a leave-one-centre-out cross validation and compared to a model based on previously discovered clinical predictors. Lastly, a combination model was built on the radiomics and clinical model.

RESULTS

A total of 620 patients were included, of which 59.2% experienced clinical benefit. The radiomics model achieved an area under the receiver operator characteristic curve (AUROC) of 0.607 [95% CI, 0.562-0.652], lower than that of the clinical model (AUROC=0.646 [95% CI, 0.600-0.692]). The combination model yielded no improvement over the clinical model in terms of discrimination (AUROC=0.636 [95% CI, 0.592-0.680]) or calibration. The output of the radiomics model was significantly correlated with three out of five input variables of the clinical model (p < 0.001).

DISCUSSION

The radiomics model achieved a moderate predictive value of clinical benefit, which was statistically significant. However, a radiomics approach was unable to add value to a simpler clinical model, most likely due to the overlap in predictive information learned by both models. Future research should focus on the application of deep learning, spectral CT-derived radiomics, and a multimodal approach for accurately predicting benefit to checkpoint inhibitor treatment in advanced melanoma.

Dimorphic cells: a common feature throughout the low nuclear grade breast neoplasia spectrum

Columnar cell lesions (CCLs) are recognized precursor lesions of the low nuclear grade breast neoplasia family. CCLs are cystic enlarged terminal duct lobular units with monotonous (monoclonal) columnar-type luminal cells. CCLs without atypia are regarded as benign and CCLs with atypia as true precursor lesions with clonal molecular changes, a certain progression risk, and an association with more advanced lesions. However, reproducibility of designating atypia in CCL is not optimal, and no objective markers of atypia have been identified, although 16q loss seems to be associated with atypical CCLs. Dimorphic ("pale") cell populations have been described in low nuclear grade ductal carcinoma in situ (DCIS) but not in CCLs and atypical ductal hyperplasia (ADH). Therefore, we searched for pale cells in CCL (N = 60), ADH (N = 41), and DCIS grade 1 (N = 84). Diagnostic criteria were derived from the WHO, and atypia was designated according to the Schnitt criteria. Pale cells occurred in 0% (0/30), 73% (22/30), 56% (23/41), and 76% (64/84) of CCLs without atypia, CCLs with atypia, ADH, and DCIS grade 1, respectively. Pale cells expressed ERα, E-cadherin and p120 and variably cyclin D1, and lacked expression of CK5 and p63. In conclusion, dimorphic "pale" cells occur throughout the low nuclear grade progression spectrum, increasing in frequency with progression. Interestingly, CCL lesions without atypia do not seem to bear showed pale cells, indicating that the presence of pale cells may serve as a diagnostic morphological feature of atypia in CCLs.

Diagnostic Accuracy of Radioactive Iodine Seed Placement in the Axilla With Sentinel Lymph Node Biopsy After Neoadjuvant Chemotherapy in Node-Positive Breast Cancer

Importance

Several less-invasive staging procedures have been proposed to replace axillary lymph node dissection (ALND) after neoadjuvant chemotherapy (NAC) in patients with initially clinically node-positive (cN+) breast cancer, but these procedures may fail to detect residual disease. Owing to the lack of high-level evidence, it is not yet clear which procedure is most optimal to replace ALND.

Objective

To determine the diagnostic accuracy of radioactive iodine seed placement in the axilla with sentinel lymph node biopsy (RISAS), a targeted axillary dissection procedure.

Design, Setting, and Participants

This was a prospective, multicenter, noninferiority, diagnostic accuracy trial conducted from March 1, 2017, to December 31, 2019. Patients were included within 14 institutions (general, teaching, and academic) throughout the Netherlands. Patients with breast cancer clinical tumor categories 1 through 4 (cT1-4; tumor diameter <2 cm and up to >5 cm or extension to the chest wall or skin) and pathologically proven positive axillary lymph nodes (ie, clinical node categories cN1, metastases to movable ipsilateral level I and/or level II axillary nodes; cN2, metastases to fixed or matted ipsilateral level I and/or level II axillary nodes; cN3b, metastases to ipsilateral level I and/or level II axillary nodes with metastases to internal mammary nodes) who were treated with NAC were eligible for inclusion. Data were analyzed from July 2020 to December 2021.

Intervention

Pre-NAC, the marking of a pathologically confirmed positive axillary lymph node with radioactive iodine seed (MARI) procedure, was performed and after NAC, sentinel lymph node biopsy (SLNB) combined with excision of the marked lymph node (ie, RISAS procedure) was performed, followed by ALND.

Main Outcomes and Measures

The identification rate, false-negative rate (FNR), and negative predictive value (NPV) were calculated for all 3 procedures: RISAS, SLNB, and MARI. The noninferiority margin of the observed FNR was 6.25% for the RISAS procedure.

Results

A total of 212 patients (median [range] age, 52 [22-77] years) who had cN+ breast cancer underwent the RISAS procedure and ALND. The identification rate of the RISAS procedure was 98.2% (223 of 227). The identification rates of SLNB and MARI were 86.4% (197 of 228) and 94.1% (224 of 238), respectively. FNR of the RISAS procedure was 3.5% (5 of 144; 90% CI, 1.38-7.16), and NPV was 92.8% (64 of 69; 90% CI, 85.37-97.10), compared with an FNR of 17.9% (22 of 123; 90% CI, 12.4%-24.5%) and NPV of 72.8% (59 of 81; 90% CI, 63.5%-80.8%) for SLNB and an FNR of 7.0% (10 of 143; 90% CI, 3.8%-11.6%) and NPV of 86.3% (63 of 73; 90% CI, 77.9%-92.4%) for the MARI procedure. In a subgroup of 174 patients in whom SLNB and the MARI procedure were successful and ALND was performed, FNR of the RISAS procedure was 2.5% (3 of 118; 90% CI, 0.7%-6.4%), compared with 18.6% (22 of 118; 90% CI, 13.0%-25.5%) for SLNB (P < .001) and 6.8% (8 of 118; 90% CI, 3.4%-11.9%) for the MARI procedure (P = .03).

Conclusions and Relevance

Results of this diagnostic study suggest that the RISAS procedure was the most feasible and accurate less-invasive procedure for axillary staging after NAC in patients with cN+ breast cancer.

Improving prediction of response to neoadjuvant treatment in patients with breast cancer by combining liquid biopsies with multiparametric MRI: protocol of the LIMA study - a multicentre prospective observational cohort study

INTRODUCTION

The response to neoadjuvant chemotherapy (NAC) in breast cancer has important prognostic implications. Dynamic prediction of tumour regression by NAC may allow for adaption of the treatment plan before completion, or even before the start of treatment. Such predictions may help prevent overtreatment and related toxicity and correct for undertreatment with ineffective regimens. Current imaging methods are not able to fully predict the efficacy of NAC. To successfully improve response prediction, tumour biology and heterogeneity as well as treatment-induced changes have to be considered. In the LIMA study, multiparametric MRI will be combined with liquid biopsies. In addition to conventional clinical and pathological information, these methods may give complementary information at multiple time points during treatment.

AIM

To combine multiparametric MRI and liquid biopsies in patients with breast cancer to predict residual cancer burden (RCB) after NAC, in adjunct to standard clinico-pathological information. Predictions will be made before the start of NAC, approximately halfway during treatment and after completion of NAC.

METHODS

In this multicentre prospective observational study we aim to enrol 100 patients. Multiparametric MRI will be performed prior to NAC, approximately halfway and after completion of NAC. Liquid biopsies will be obtained immediately prior to every cycle of chemotherapy and after completion of NAC. The primary endpoint is RCB in the surgical resection specimen following NAC. Collected data will primarily be analysed using multivariable techniques such as penalised regression techniques.

ETHICS AND DISSEMINATION

Medical Research Ethics Committee Utrecht has approved this study (NL67308.041.19). Informed consent will be obtained from each participant. All data are anonymised before publication. The findings of this study will be submitted to international peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT04223492.

Imaging to predict checkpoint inhibitor outcomes in cancer. A systematic review

BACKGROUND

Checkpoint inhibition has radically improved the perspective for patients with metastatic cancer, but predicting who will not respond with high certainty remains difficult. Imaging-derived biomarkers may be able to provide additional insights into the heterogeneity in tumour response between patients. In this systematic review, we aimed to summarise and qualitatively assess the current evidence on imaging biomarkers that predict response and survival in patients treated with checkpoint inhibitors in all cancer types.

METHODS

PubMed and Embase were searched from database inception to 29th November 2021. Articles eligible for inclusion described baseline imaging predictive factors, radiomics and/or imaging machine learning models for predicting response and survival in patients with any kind of malignancy treated with checkpoint inhibitors. Risk of bias was assessed using the QUIPS and PROBAST tools and data was extracted.

RESULTS

In total, 119 studies including 15,580 patients were selected. Of these studies, 73 investigated simple imaging factors. 45 studies investigated radiomic features or deep learning models. Predictors of worse survival were (i) higher tumour burden, (ii) presence of liver metastases, (iii) less subcutaneous adipose tissue, (iv) less dense muscle and (v) presence of symptomatic brain metastases. Hazard rate ratios did not exceed 2.00 for any predictor in the larger and higher quality studies. The added value of baseline fluorodeoxyglucose positron emission tomography parameters in predicting response to treatment was limited. Pilot studies of radioactive drug tracer imaging showed promising results. Reports on radiomics were almost unanimously positive, but numerous methodological concerns exist.

CONCLUSIONS

There is well-supported evidence for several imaging biomarkers that can be used in clinical decision making. Further research, however, is needed into biomarkers that can more accurately identify which patients who will not benefit from checkpoint inhibition. Radiomics and radioactive drug labelling appear to be promising approaches for this purpose.

Deep learning-based breast cancer grading and survival analysis on whole-slide histopathology images

Breast cancer tumor grade is strongly associated with patient survival. In current clinical practice, pathologists assign tumor grade after visual analysis of tissue specimens. However, different studies show significant inter-observer variation in breast cancer grading. Computer-based breast cancer grading methods have been proposed but only work on specifically selected tissue areas and/or require labor-intensive annotations to be applied to new datasets. In this study, we trained and evaluated a deep learning-based breast cancer grading model that works on whole-slide histopathology images. The model was developed using whole-slide images from 706 young (< 40 years) invasive breast cancer patients with corresponding tumor grade (low/intermediate vs. high), and its constituents nuclear grade, tubule formation and mitotic rate. The performance of the model was evaluated using Cohen's kappa on an independent test set of 686 patients using annotations by expert pathologists as ground truth. The predicted low/intermediate (n = 327) and high (n = 359) grade groups were used to perform survival analysis. The deep learning system distinguished low/intermediate versus high tumor grade with a Cohen's Kappa of 0.59 (80% accuracy) compared to expert pathologists. In subsequent survival analysis the two groups predicted by the system were found to have a significantly different overall survival (OS) and disease/recurrence-free survival (DRFS/RFS) (p < 0.05). Univariate Cox hazard regression analysis showed statistically significant hazard ratios (p < 0.05). After adjusting for clinicopathologic features and stratifying for molecular subtype the hazard ratios showed a trend but lost statistical significance for all endpoints. In conclusion, we developed a deep learning-based model for automated grading of breast cancer on whole-slide images. The model distinguishes between low/intermediate and high grade tumors and finds a trend in the survival of the two predicted groups.

Elevated miR-29c-5p Expression in Nipple Aspirate Fluid Is Associated with Extremely High Mammographic Breast Density

Simple Summary

High mammographic density is a known risk factor for breast cancer. However, the underlying mechanisms of high mammographic density development and breast cancer are unknown. MicroRNAs are potential biomarkers indicative of carcinogenesis and can be assessed in nipple aspirate fluid. We used nipple aspirate fluid from women with very low and extremely high mammographic density to examine differences in expression of multiple miRNAs between both extremes in the spectrum of mammographic density. We found that hsa-miR-29c-5p was upregulated in an extremely high mammographic density context and potential targets were identified that might provide clues of the relationship between high mammographic density and breast cancer risk. Understanding the relationship between high mammographic density and breast cancer is of great value for early breast cancer diagnosis and treatment. With our research we provide new insight into this relationship and further research could determine the effects of dysregulated hsa-miR-29c-5p on the identified candidate targets.

Abstract

High mammographic density (MD) is associated with an increased risk of breast cancer, however the underlying mechanisms are largely unknown. This research aimed to identify microRNAs (miRNAs) that play a role in the development of extremely dense breast tissue. In the discovery phase, 754 human mature miRNAs were profiled in 21 extremely high MD- and 20 very low MD-derived nipple aspirate fluid (NAF) samples from healthy women. In the validation phase, candidate miRNAs were assessed in a cohort of 89 extremely high MD and 81 very low MD NAF samples from healthy women. Independent predictors of either extremely high MD or miRNA expression were identified by logistic regression and linear regression analysis, respectively. mRNA targets and pathways were identified through miRTarBase, TargetScan, and PANTHER pathway analysis. Statistical analysis identified four differentially expressed miRNAs during the discovery phase. During the validation, linear regression (p = 0.029; fold change = 2.10) and logistic regression (p = 0.048; odds ratio = 1.38) showed that hsa-miR-29c-5p was upregulated in extremely high MD-derived NAF. Identified candidate mRNA targets of hsa-miR-29c-5p are CFLAR, DNMT3A, and PTEN. Further validation and exploration of targets and downstream pathways of has-miR-29c-5p will provide better insight into the processes involved in the development of high MD and in the associated increased risk of breast cancer.

Patient-centered research: how do women tolerate nipple fluid aspiration as a potential screening tool for breast cancer?

Background

Nipple fluid aspiration (NFA) is a technique to acquire nipple aspirate fluid (NAF), which is considered a rich source of breast-specific biomarkers. Originating directly from the mammary ducts, this liquid biopsy can offer insight into the process of carcinogenesis at its earliest stage and therefore could be of added value to the current imaging-based breast cancer screening tools. With that in mind, it is necessary to know how well NFA is tolerated.

Aim

To evaluate the participants’ tolerability of NFA compared to breast imaging screening methods and blood draws.

Materials and methods

Three cohorts of women underwent NFA: healthy women (n = 190), women diagnosed with breast cancer (n = 137) and women at high risk of developing breast cancer (n = 48). A 0–10 discomfort score of NFA, mammography, breast MRI and blood draws, was filled in at the study visits, which took place once or annually.

Results

The median discomfort rate of NFA was 1, which was significantly lower than the median discomfort of mammography and breast MRI (5 and 3, respectively, p < 0.001), but significantly higher than median discomfort for blood draws (0, p < 0.001). The great majority of women would undergo the procedure again (98%) and recommend it to others (97%).

Conclusion

This study shows that NFA was well tolerated by healthy women, women diagnosed with breast cancer and high-risk women. This makes NFA a feasible method to pursue as a potential future breast cancer early detection tool, based on resident biomarkers.

Trial registration

NL41845.041.12, NL57343.041.16 and NL11690.041.06 in trialregister.nl.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09795-8.

Clinical significance and molecular annotation of cellular morphometric subtypes in lower-grade gliomas discovered by machine learning

BACKGROUND

Lower-grade gliomas (LGG) are heterogeneous diseases by clinical, histological, and molecular criteria. We aimed to personalize the diagnosis and therapy of LGG patients by developing and validating robust cellular morphometric subtypes (CMS) and to uncover the molecular signatures underlying these subtypes.

METHODS

Cellular morphometric biomarkers (CMBs) were identified with artificial intelligence technique from TCGA-LGG cohort. Consensus clustering was used to define CMS. Survival analysis was performed to assess the clinical impact of CMBs and CMS. A nomogram was constructed to predict 3- and 5-year overall survival (OS) of LGG patients. Tumor mutational burden (TMB) and immune cell infiltration between subtypes were analyzed using the Mann-Whitney U test. The double-blinded validation for important immunotherapy-related biomarkers was executed using immunohistochemistry (IHC).

RESULTS

We developed a machine learning (ML) pipeline to extract CMBs from whole-slide images of tissue histology; identifying and externally validating robust CMS of LGGs in multicenter cohorts. The subtypes had independent predicted OS across all three independent cohorts. In the TCGA-LGG cohort, patients within the poor-prognosis subtype responded poorly to primary and follow-up therapies. LGGs within the poor-prognosis subtype were characterized by high mutational burden, high frequencies of copy number alterations, and high levels of tumor-infiltrating lymphocytes and immune checkpoint genes. Higher levels of PD-1/PD-L1/CTLA-4 were confirmed by IHC staining. In addition, the subtypes learned from LGG demonstrate translational impact on glioblastoma (GBM).

CONCLUSIONS

We developed and validated a framework (CMS-ML) for CMS discovery in LGG associated with specific molecular alterations, immune microenvironment, prognosis, and treatment response.

Implementation of Artificial Intelligence in Diagnostic Practice as a Next Step after Going Digital: The UMC Utrecht Perspective

Building on a growing number of pathology labs having a full digital infrastructure for pathology diagnostics, there is a growing interest in implementing artificial intelligence (AI) algorithms for diagnostic purposes. This article provides an overview of the current status of the digital pathology infrastructure at the University Medical Center Utrecht and our roadmap for implementing AI algorithms in the next few years.

Prognostic Value of Stromal Tumor-Infiltrating Lymphocytes in Young, Node-Negative, Triple-Negative Breast Cancer Patients Who Did Not Receive (neo)Adjuvant Systemic Therapy

PURPOSE

Triple-negative breast cancer (TNBC) is considered aggressive, and therefore, virtually all young patients with TNBC receive (neo)adjuvant chemotherapy. Increased stromal tumor-infiltrating lymphocytes (sTILs) have been associated with a favorable prognosis in TNBC. However, whether this association holds for patients who are node-negative (N0), young (< 40 years), and chemotherapy-naïve, and thus can be used for chemotherapy de-escalation strategies, is unknown.

METHODS

We selected all patients with N0 TNBC diagnosed between 1989 and 2000 from a Dutch population–based registry. Patients were age < 40 years at diagnosis and had not received (neo)adjuvant systemic therapy, as was standard practice at the time. Formalin-fixed paraffin-embedded blocks were retrieved (PALGA: Dutch Pathology Registry), and a pathology review including sTILs was performed. Patients were categorized according to sTILs (< 30%, 30%-75%, and ≥ 75%). Multivariable Cox regression was performed for overall survival, with or without sTILs as a covariate. Cumulative incidence of distant metastasis or death was analyzed in a competing risk model, with second primary tumors as competing risk.

RESULTS

sTILs were scored for 441 patients. High sTILs (≥ 75%; 21%) translated into an excellent prognosis with a 15-year cumulative incidence of a distant metastasis or death of only 2.1% (95% CI, 0 to 5.0), whereas low sTILs (< 30%; 52%) had an unfavorable prognosis with a 15-year cumulative incidence of a distant metastasis or death of 38.4% (32.1 to 44.6). In addition, every 10% increment of sTILs decreased the risk of death by 19% (adjusted hazard ratio: 0.81; 95% CI, 0.76 to 0.87), which are an independent predictor adding prognostic information to standard clinicopathologic variables (χ² = 46.7, P < .001).

CONCLUSION

Chemotherapy-naïve, young patients with N0 TNBC with high sTILs (≥ 75%) have an excellent long-term prognosis. Therefore, sTILs should be considered for prospective clinical trials investigating (neo)adjuvant chemotherapy de-escalation strategies.

Young cancer patients with TNBC and high sTILs have an excellent outcome, even without systemic treatment