Cancer Subtypes Research Articles

A whole-slide foundation model for digital pathology from real-world data.

Digital pathology poses unique computational challenges, as a standard gigapixel slide may comprise tens of thousands of image tiles1-3. Prior models have often resorted to subsampling a small portion of tiles for each slide, thus missing the important slide-level context4. Here we present Prov-GigaPath, a whole-slide pathology foundation model pretrained on 1.3 billion 256 × 256 pathology image tiles in 171,189 whole slides from Providence, a large US health network comprising 28 cancer centres. The slides originated from more than 30,000 patients covering 31 major tissue types. To pretrain Prov-GigaPath, we propose GigaPath, a novel vision transformer architecture for pretraining gigapixel pathology slides. To scale GigaPath for slide-level learning with tens of thousands of image tiles, GigaPath adapts the newly developed LongNet5 method to digital pathology. To evaluate Prov-GigaPath, we construct a digital pathology benchmark comprising 9 cancer subtyping tasks and 17 pathomics tasks, using both Providence and TCGA data6. With large-scale pretraining and ultra-large-context modelling, Prov-GigaPath attains state-of-the-art performance on 25 out of 26 tasks, with significant improvement over the second-best method on 18 tasks. We further demonstrate the potential of Prov-GigaPath on vision-language pretraining for pathology7,8 by incorporating the pathology reports. In sum, Prov-GigaPath is an open-weight foundation model that achieves state-of-the-art performance on various digital pathology tasks, demonstrating the importance of real-world data and whole-slide modelling.

CCDC12 gene methylation in peripheral blood as a potential biomarker for breast cancer detection.

Aberrant DNA methylation has been identified as biomarkers for breast cancer detection. Coiled-coil domain containing 12 gene (CCDC12) implicated in tumorigenesis. This study aims to investigate the potential of blood-based CCDC12 methylation for breast cancer detection. DNA methylation level of CpG sites (Cytosine-phosphate Guanine dinucleotides) in CCDC12 gene was measured by mass spectrometry in 255 breast cancer patients, 155 patients with benign breast nodules and 302 healthy controls. The association between CCDC12 methylation and breast cancer risk was evaluated by logistic regression and receiver operating characteristic curve analysis. A total of eleven CpG sites were analyzed. The CCDC12 methylation levels were higher in breast cancer patients. Compared to the lowest tertile of methylation level in CpG_6,7, CpG_10 and CpG_11, the highest quartile was associated with 82%, 91%, and 95% increased breast cancer risk, respectively. The CCDC12 methylation levels were associated with estrogen receptor (ER) and human epidermal growth factor 2 (HER2) status. In ER-negative and HER2-positive (ER-/HER2+) breast cancer subtype, the combination of four sites CpG_2, CpG_5, CpG_6,7 and CpG_11 methylation levels could distinguish ER-/HER2+ breast cancer from the controls (AUC = 0.727). The hypermethylation levels of CCDC12 in peripheral blood could be used for breast cancer detection.

Digital Mammography (DM) vs. Dynamic Contrast Enhancement—Magnetic Resonance Imaging (DCE-MRI) in Microcalcifications Assessment: A Radiological–Pathological Comparison

The aim of this study was to compare the characteristics of breast microcalcification on digital mammography (DM) with the histological and molecular subtypes of breast cancer and to identify the predictive value of DM and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in assessing microcalcifications for radiologic–pathologic correlation. We relied on our prospectively maintained database of suspicious microcalcifications on DM, from which data were retrospectively collected between January 2020 and April 2023. We enrolled 158 patients, all of whom were subjected to biopsy. Additionally, 63 patients underwent breast DCE-MRI. Microcalcifications with a linear branched morphology were correlated with malignancies (p < 0.001), among which an association was highlighted between triple negatives (TNs) and segmental distribution (p < 0.001). Amorphous calcifications were correlated with atypical ductal hyperplasia (ADH) (p = 0.013), coarse heterogeneous (p < 0.001), and fine-pleomorphic (p = 0.008) with atypical lobular hyperplasia (ALH) and fine pleomorphic (p = 0.009) with flat epithelial atypia (FEA). Regarding DCE-MRI, no statistical significance was observed between non-mass lesions and ductal carcinoma in situ (DCIS). Concerning mass lesions, three were identified as DCIS and five as invasive ductal carcinoma (IDC). In conclusion, microcalcifications assessed in DM exhibit promising predictive characteristics concerning breast lesion subtypes, leading to a reduction in diagnostic times and further examination costs, thereby enhancing the clinical management of patients.

Patterns of cytotoxic T-cell densities in immunogenic endometrial cancers reveal a potential mechanism for differences in immunotherapy efficacy

ObjectiveTo explore the impact of molecular subtype in endometrial cancer (EC) on CD8+T cell densities. Furthermore, this work will test the assumption that all mismatch repair deficient (MMRd) tumours are...

Role of ICAM-1 in triple-negative breast cancer.

Intercellular adhesion molecule-1 (ICAM-1) is related to the occurrence and development of a variety of tumors. However, the role of ICAM-1 in the regulation of growth, metastasis, and clinical prognosis of the specific molecular subtypes of breast cancer, triple-negative breast cancer (TNBC), remains to be elucidated. This study explored the role of ICAM-1 in breast cancer and its triple-negative subtypes by systematic bioinformatics methods. The results showed that the expression of ICAM-1 in breast cancer tissues was significantly higher than that in normal tissues, especially in TNBC subtypes. In breast cancer, ICAM-1 mainly activates pathways related to apoptosis and epithelial-mesenchymal transition, while its overexpression in TNBC is associated with inflammatory response, apoptosis, and other processes. TNBC patients displaying higher ICAM-1 expression demonstrate enhanced responses to immunotherapy. High ICAM-1 expression is sensitive to drugs targeting tumor cell proliferation, apoptosis, and angiogenesis. In conclusion, breast cancer is characterized by significantly high expression of ICAM-1, with TNBC subtypes expressing ICAM-1 at much higher levels than other subtypes. The diagnosis, prognosis, development, distant metastases, and immunotherapy of TNBC are correlated with high expression of ICAM-1. This research provides available data for the further study of the diagnosis and treatment of TNBC.

Unsupervised mutual transformer learning for multi-gigapixel Whole Slide Image classification

The classification of gigapixel Whole Slide Images (WSIs) is an important task in the emerging area of computational pathology. There has been a surge of interest in deep learning models for WSI classification with clinical applications such as cancer detection or prediction of cellular mutations. Most supervised methods require expensive and labor-intensive manual annotations by expert pathologists. Weakly supervised Multiple Instance Learning (MIL) methods have recently demonstrated excellent performance; however, they still require large-scale slide-level labeled training datasets that require a careful inspection of each slide by an expert pathologist. In this work, we propose a fully unsupervised WSI classification algorithm based on mutual transformer learning. The instances (i.e., patches) from gigapixel WSIs are transformed into a latent space and then inverse-transformed to the original space. Using the transformation loss, pseudo labels are generated and cleaned using a transformer label cleaner. The proposed transformer-based pseudo-label generator and cleaner modules mutually train each other iteratively in an unsupervised manner. A discriminative learning mechanism is introduced to improve normal versus cancerous instance labeling. In addition to the unsupervised learning, we demonstrate the effectiveness of the proposed framework for weakly supervised learning and cancer subtype classification as downstream analysis. Extensive experiments on four publicly available datasets show better performance of the proposed algorithm compared to the existing state-of-the-art methods.

Exploring novel approaches in the systemic therapy of low-grade serous carcinoma of the ovary: a literature review

By presenting a comprehensive analysis of low-grade serous carcinomas (LGSCs), a subset of epithelial ovarian cancers, this review delves into their distinct molecular characteristics, clinicopathological features and systemic therapy options, emphasizing their differences from high-grade serous carcinomas (HGSCs). Notably, LGSCs exhibit prevalent RAS/RAF/MEK/MAPK pathway activation, KRAS and BRAF mutations, and infrequent p53 mutations. While chemotherapy is commonly employed, LGSCs display lower responsiveness compared to HGSCs. Hormone therapy, particularly endocrine maintenance therapy, is explored due to the higher estrogen receptor expression. Novel therapeutic approaches involving CDK4/6 inhibitors, MEK inhibitors, and antiangiogenic agents like bevacizumab are also investigated. Ongoing clinical trials are striving to enhance LGSC treatment strategies, offering valuable insights for future therapeutic advancements in this challenging ovarian cancer subtype.

Machine learning identifies the role of SMAD6 in the prognosis and drug susceptibility in bladder cancer

BackgroundBladder cancer (BCa) is among the most prevalent malignant tumors affecting the urinary system. Due to its highly recurrent nature, standard treatments such as surgery often fail to significantly improve patient prognosis. Our research aims to predict prognosis and identify precise therapeutic targets for novel treatment interventions.MethodsWe collected and screened genes related to the TGF-β signaling pathway and performed unsupervised clustering analysis on TCGA-BLCA samples based on these genes. Our analysis revealed two novel subtypes of bladder cancer with completely different biological characteristics, including immune microenvironment, drug sensitivity, and more. Using machine learning classifiers, we identified SMAD6 as a hub gene contributing to these differences and further investigated the role of SMAD6 in bladder cancer in the single-cell transcriptome data. Additionally, we analyzed the relationship between SMAD6 and immune checkpoint genes. Finally, we performed a series of in vitro assays to verify the function of SMAD6 in bladder cancer cell lines.ResultsWe have revealed two novel subtypes of bladder cancer, among which C1 exhibits a worse prognosis, lower drug sensitivity, a more complex tumor microenvironment, and a ‘colder’ immune microenvironment compared to C2. We identified SMAD6 as a key gene responsible for the differences and further explored its impact on the molecular characteristics of bladder cancer. Through in vitro experiments, we found that SMAD6 promoted the prognosis of BCa patients by inhibiting the proliferation and migration of BCa cells.ConclusionOur study reveals two novel subtypes of BCa and identifies SMAD6 as a highly promising therapeutic target.

Risk factor analysis and nomogram development and verification for medullary carcinoma of the colon using SEER database

Medullary Carcinoma of the Colon (MCC) is a rare histological subtype of colon cancer, and there is currently no recognized optimal treatment plan for it, with its prognosis remaining unclear. The aim of this study is to analyze the independent prognostic factors for MCC patients and develop and validate nomograms to predict overall survival (OS). A total of 760 patients newly diagnosed with MCC from 2004 to 2020 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. All patients were randomly allocated to a training group and a validation group in a 7:3 ratio. Univariate and multivariable Cox regression analyses were conducted to identify prognostic factors and construct nomograms. The nomogram prediction model was evaluated and validated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). The study found that elderly women are more susceptible to MCC, and the ascending colon and cecum are the most common sites of involvement. MCC is poorly differentiated, with stages II and III being the most common. Surgery is the primary treatment for MCC. The prognosis for patients with stage IV MCC is poor, with a median survival time of only 10 months. Independent prognostic factors for MCC include age, N stage, M stage, surgery, chemotherapy, and tumor size. Among them, age < 75 years and completion of chemotherapy were protective factors for colon medullary carcinoma, while N2 (HR = 2.18, 95%CI 1.40–3.38), M1 (HR = 3.31, 95%CI 2.01–5.46), no surgery (HR = 27.94, 95%CI 3.69–211.75), and tumor diameter > 7 cm (HR = 1.66, 95%CI 1.20–2.30) were risk factors for colon medullary carcinoma. The results of ROC, AUC, calibration curves, and DCA demonstrate that the nomogram prediction model exhibits good predictive performance. We have updated the demographic characteristics of colon medullary carcinoma and identified age, N staging, M staging, surgery, chemotherapy and tumor size as independent prognostic factors for colon medullary carcinoma. Additionally, we have established nomograms for prognostic prediction. These nomograms can provide personalized predictions and serve as valuable references for clinical decision-making.

Pathological complete response with FOLFIRINOX therapy for recurrence of pancreatic acinar cell carcinoma.

Pancreatic acinar cell carcinoma (PACC) is a very rare subtype of pancreatic cancer. Due to small number of patients, no standard chemotherapy protocol has been established. We experienced an extremely rare case of PACC with liver metastasis that showed a pathological complete response after modified FOLFIRINOX (mFFX) therapy. A 42-year-old man who underwent distal pancreatectomy for an 80mm tumor at the pancreatic tail 3years ago was referred to our hospital in September 2017 for the treatment of a recurrent liver tumor. Percutaneous biopsy revealed an acinar-neuroendocrine carcinoma, similar to the surgical specimen. He received eight cycles of irinotecan plus cisplatin chemotherapy. However, the tumor increased in size, and treatment was switched to mFFX therapy. The tumor in the liver shrank remarkably after nine cycles of mFFX therapy. Conversion surgery was selected, and the patient underwent hepatic left and caudate lobectomy 8months after administration of mFFX. The resected specimen showed no viable tumor cells, indicating a pathological complete response. The histological diagnosis was reconsidered, and PACC was finally diagnosed via an additional immunohistological review. The patient has remained well with no recurrence for 6years after surgery. This study is the first to report a case of pathological complete response with mFFX therapy for the recurrence of PACC.

Assessing clinical pathological characteristics and gene expression patterns associated with hepatoid adenocarcinoma of the stomach.

The objective of this study is to assess the clinical pathological attributes of Hepatoid Adenocarcinoma of the Stomach (HAS) and to delineate the differential diagnostic considerations about it. The investigation involved analyzing 31 HAS cases using histomorphological assessment, immunohistochemical profiling, and relevant gene detection methodologies. Among the 31 HAS cases, 9 (29.0%) were of trabecular hepatoid adenocarcinoma of the stomach, 7 (22.6%) were of glandular hepatoid adenocarcinoma of the stomach, 4 (12.9%) were of nesting hepatoid adenocarcinoma of the stomach, 3 (9.7%) were of clear cell hepatoid adenocarcinoma of the stomach, and 8 (25.8%) were of diverse hepatoid adenocarcinoma of the stomach. Of these 31 cases, 24 were male, accounting for 77.4% of the cases. Serum alpha-fetoprotein (AFP) levels were notably elevated, with radioimmunoassay results reaching 1240ng/ml; 28 out of 31 cases had AFP levels below 25µg/l, accounting for 90.3%. Related genes: HER2 protein indicated positive expression on the cell membrane in 35.5% (11/31) of the cases; HER2 gene amplification detected by the FISH technique was 12.9% (4/31). Tumoral stromal lymphocytes exhibited a PD-1 positive expression rate of 58.1% (18/31). In gastric cancer tissues, the PD-L1 positive rate was 45.1% (14/31). HAS represents a distinctive subtype of gastric cancer with a propensity for mimicking other forms of tumors, underscoring the significance of discerning its unique histopathological attributes for accurate differential diagnosis and tailored therapeutic interventions.

Photodynamic therapy in the treatment of non-melanoma skin cancer: A literature review

Objective: The following study aims to analyze the mechanism of action, efficacy, safety and recent trends in the use of photodynamic therapy (PDT) as a therapeutic approach in the treatment of non-melanoma skin cancer. In addition, it seeks to provide a comprehensive overview of the current state of knowledge on the subject, highlighting its use and availability in the Brazilian scenario. Methods: The research was carried out using a literature review based on data published in Periódicos CAPES, Biblioteca Virtual de Saúde (BVS) and UpToDate. Results: PDT is a technique that has already been consolidated globally and has several advantages in the treatment of non-melanoma skin cancer, as well as actinic keratoses, even in comprehensive cases. PDT is considered a non-invasive, fast, safe method, with few side effects, providing rapid recovery and being well tolerated by patients. It has a significant cure rate and excellent aesthetic results, differing from other treatments often cited for their disadvantages, such as undesirable scars. Conclusion: It is crucial to further explore the benefits of PDT, considering its application in different subtypes of non-melanoma skin cancer and optimizing protocols to expand its clinical application. As a promising innovation, the technology has the prospect of contributing to improving the quality of life of patients affected by this specific type of skin cancer.

Abstract IA003: Molecular subtypes and clinical benefit from neoadjuvant chemotherapy: A ten-year update

Abstract Ten years ago TCGA and two private groups reported that muscle-invasive bladder cancers (MIBCs) could be grouped into basal and luminal molecular subtypes that shared features with the corresponding subtypes of breast cancer. These and earlier studies by the group at Lund University demonstrated that molecular subtype membership was prognostic: patients whose tumors were assigned to basal/squamous subtypes had shorter survival than did patients whose tumors were assigned to the luminal subtypes, and these relationships were confirmed in subsequent studies. In addition, one of the studies included tumors from patients treated with neoadjuvant cisplatin-based combination chemotherapy (NAC), where patients whose tumors were infiltrated with smooth muscle cells and fibroblasts (the MD Anderson p53-like subtype) had the lowest response rates. Parallel comparisons of patients who either did or did not receive NAC concluded that patients with basal tumors derived the most clinical benefit in terms of disease-specific or overall survival. Thus, in addition to being prognostic, there was a suggestion that molecular subtypes might also be used to predict resistance to NAC. This work led to the design of two large collaborative projects that were designed to validate these observations and the conclusion that inactivating mutations in several DNA damage and repair (DDR) genes were also associated with response. One leveraged the S1314 Phase-2 “CoXEN” trial that was designed to prospectively validate another gene expression-based biomarker, and the other exploited pretreatment samples from the CALGB/Alliance 90601 Phase-3 trial of gemcitabine/cisplatin with or without bevacizumab in patients with advanced or metastatic disease. Comparisons of response rates as a function of molecular subtype membership in S1314 failed to validate the original link between the MD Anderson p53-like subtype and resistance, and patients with basal/squamous tumors in 90601 did not have better outcomes than did patients with luminal tumors. Thus, while the prognostic value of molecular subtype membership was confirmed, the predictive value was not. Developing biomarkers to predict response to chemotherapy remains a challenge not only for bladder cancer but also for other solid and hematopoietic malignancies. It seems likely that success will require the integration of measurements using multiple platforms, including liquid biopsies and others. The exciting results of the EV-302 clinical trial of enfortumab vedotin plus pembrolizumab have shifted the focus of biomarker work to these and other novel agents. Citation Format: David J McConkey. Molecular subtypes and clinical benefit from neoadjuvant chemotherapy: A ten-year update [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2024 May 17-20; Charlotte, NC. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(10_Suppl):Abstract nr IA003.

Luminal androgen receptor subtype and tumor-infiltrating lymphocytes groups based on triple-negative breast cancer molecular subclassification.

In our previous study, we developed a triple-negative breast cancer (TNBC) subtype classification that correlated with the TNBC molecular subclassification. In this study, we aimed to evaluate the predictor variables of this subtype classification on the whole slide and to validate the model's performance by using an external test set. We explored the characteristics of this subtype classification and investigated genomic alterations, including genomic scar signature scores. First, TNBC was classified into the luminal androgen receptor (LAR) and non-luminal androgen receptor (non-LAR) subtypes based on the AR Allred score (≥ 6 and < 6, respectively). Then, the non-LAR subtype was further classified into the lymphocyte-predominant (LP), lymphocyte-intermediate (LI), and lymphocyte-depleted (LD) groups based on stromal tumor-infiltrating lymphocytes (TILs) (< 20%, > 20% but < 60%, and ≥ 60%, respectively). This classification showed fair agreement with the molecular classification in the test set. The LAR subtype was characterized by a high rate of PIK3CA mutation, CD274 (encodes PD-L1) and PDCD1LG2 (encodes PD-L2) deletion, and a low homologous recombination deficiency (HRD) score. The non-LAR LD TIL group was characterized by a high frequency of NOTCH2 and MYC amplification and a high HRD score.

Racial and survival disparities in inflammatory breast cancer (IBC) and non-IBC: a population-based study focused on Native Hawaiians and other Pacific Islanders

BackgroundIt is well known that race is an independent predictor of breast cancer mortality and advanced stage at diagnosis. Inflammatory breast cancer (IBC) is the most aggressive type of breast cancer and has distinct clinical and biological features. Previous studies have shown that Blacks have a higher incidence of IBC than Whites. However, the proportion of IBC and the role of race on prognosis in Native Hawaiian and other Pacific Islander (NH/PI) populations with breast cancer are poorly understood. In this study, we aimed to examine the proportion of IBC to non-IBC in NH/PIs and to identify the clinicopathological, biological, and socioeconomic factors associated with the overall survival of NH/PIs compared to other races.MethodsUtilizing a comprehensive cancer registry from the largest hospital in Hawaii, newly diagnosed primary invasive breast cancer patients diagnosed between 2000 and 2018 were identified. Univariate and multivariate Cox proportional hazards models were used to test the association between race and clinical outcomes. Variables with P-values &amp;lt;0.05 in the univariate analysis and race (variable of interest) were included in a multivariate analysis.ResultsThe cohort included 3691 patients, 60 of whom had IBC. NH/PI race had the highest proportion of IBC compared to other races (3.44%) but was not found to be an independent poor prognostic factor in IBC (HR 1.17 [95%CI 0.26-5.22]). Conversely, NH/PI race was associated with worse survival outcomes in patients with non-IBC (HR 1.65 [95%CI, 1.14-2.39]) along with other factors such as lack of insurance, underinsured status, triple-negative breast cancer (TNBC) subtype, age, and advanced clinical stage.ConclusionsThe findings of this study highlight that NH/PIs had higher rates of IBC and inferior survival in non-IBC compared to other races but not in IBC. It is essential to disaggregate NH/PI race from Asians in future population-based research studies. Further research is needed to understand the factors contributing to higher rates of IBC and poor survival outcomes in NH/PIs with non-IBC as well as targeted interventions to improve breast cancer outcomes in this population to ultimately help improve survival rates and reduce health inequities in NH/PIs with breast cancer.

Associations between chronic obstructive pulmonary disease and ten common cancers: novel insights from Mendelian randomization analyses.

Chronic obstructive pulmonary disease (COPD) is a significant global health issue, suspected to elevate the risk for various cancers. This study sought to discern whether COPD serves as a risk marker or a causative factor for prevalent cancers. We employed univariable MR (UVMR) analyses to investigate the causal relationship between COPD and the top ten common cancers. Sensitivity analyses were performed to validate the main findings. Multivariable MR (MVMR) and two-step MR analyses were also conducted. False-discovery-rate (FDR) was used to correct multiple testing bias. The UVMR analysis demonstrated notable associations between COPD and lung cancer (odds ratio [OR] = 1.42, 95%CI 1.15-1.77, FDR = 6.37 × 10-3). This relationship extends to lung cancer subtypes such as squamous cell carcinoma (LUSC), adenocarcinoma (LUAD), and small cell lung cancer (SCLC). A tentative link was also identified between COPD and bladder cancer (OR = 1.53, 95%CI 1.03-2.28, FDR = 0.125). No significant associations were found between COPD and other types of cancer. The MVMR analysis that adjusted for smoking, alcohol drinking, and body mass index did not identify any significant causal relationships between COPD and either lung or bladder cancer. However, the two-step MR analysis indicates that COPD mediated 19.2% (95% CI 12.7-26.1%), 36.1% (24.9-33.2%), 35.9% (25.7-34.9%), and 35.5% (26.2-34.8%) of the association between smoking and overall lung cancer, as well as LUAD, LUSC, and SCLC, respectively. COPD appears to act more as a risk marker than a direct cause of prevalent cancers. Importantly, it partially mediates the connection between smoking and lung cancer, underscoring its role in lung cancer prevention strategies.

Forget Me Not: Incidental Findings on Breast MRI.

With the growing utilization and expanding role of breast MRI, breast imaging radiologists may encounter an increasing number of incidental findings beyond the breast and axilla. Breast MRI encompasses a large area of anatomic coverage extending from the lower neck to the upper abdomen. While most incidental findings on breast MRI are benign, identifying metastatic disease can have a substantial impact on staging, prognosis, and treatment. Breast imaging radiologists should be familiar with common sites, MRI features, and breast cancer subtypes associated with metastatic disease to assist in differentiating malignant from benign findings. Furthermore, detection of malignancies of nonbreast origin as well as nonmalignant, but clinically relevant, incidental findings can significantly impact clinical management and patient outcomes. Breast imaging radiologists should consistently follow a comprehensive search pattern and employ techniques to improve the detection of these important incidental findings.

Abstract IA022: AI in bladder cancer pathology and research: What can we expect and what not?

Abstract Artificial intelligence (AI) applications are rapidly evolving, disruptive technologies that recently attracted tremendous public awareness including euphoria, bull runs at stock exchanges but also criticism and skepticism. Pathology, a crucial clinical diagnostic discipline, faces significant challenges despite its critical role and broad scope. A notable issue is the declining interest among medical graduates in pursuing further training in Surgical Pathology and Molecular Pathology. This disinterest is compounded by a trend towards part-time work and the aging demographic in Western industrial nations, which increases the demand for precise cancer diagnoses, molecular pathology and advanced oncological treatments. As the need for skilled pathologists grows, the availability of these professionals is steadily decreasing. Furthermore, political policies in heavily regulated healthcare systems (e.g., Germany) are exacerbating the shortage by limiting residency and specialist training positions despite the growing need. Adding to the reluctance among medical graduates to consider pathology as discipline is the looming “threat”” of replacing the field with Artificial Intelligence (AI) technologies. However, historical precedents suggest that necessity often spurs significant innovation. AI's role in pathology is expanding, reshaping the field with new technological advancements. AI, broadly encompassing various computational algorithms designed to perform tasks typically requiring human intelligence such as learning, reasoning, and pattern recognition, is now being applied extensively across different domains including medical diagnostics. Recent implementations in pathology include AI-driven algorithms that automate processes such as the Gleason grading of prostate biopsies, lymph node metastasis detection, detection of molecular bladder cancer subtypes or grading of kidney cancer showing high accuracy levels, speed and reproducibility in delivering results. These tools, while they do not replace pathologists, significantly reduce their workload by automating routine tasks, thus freeing up time for more complex diagnostic activities or simply dealing with the increasing workload. Despite the exciting possibilities, the use of AI in predicting molecular alterations, such as FGFR3 mutations in bladder cancer, faces limitations due to insufficient sensitivity and specificity, indicating that such technologies are not yet suitable for screening purposes. In conclusion, AI is increasingly vital in addressing the challenges of modern pathology, particularly in compensating for the shortage of pathologists. As technology advances, its integration into clinical practice offers promising solutions to enhance diagnostic accuracy and efficiency in uropathology, paving the way for more personalized and effective patient care. Citation Format: Markus Eckstein. AI in bladder cancer pathology and research: What can we expect and what not? [abstract]. In: Proceedings of the AACR Special Conference on Bladder Cancer: Transforming the Field; 2024 May 17-20; Charlotte, NC. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(10_Suppl):Abstract nr IA022.

Multi-targeted nanoarrays for early broad-spectrum detection of lung cancer based on blood biopsy of tumor exosomes

Liquid biopsies utilizing tumor exosomes offer a noninvasive approach for cancer diagnosis. However, validation studies consistently report that in the early stages of cancer, the secretion of exosomes by cancer cells is relatively low, while bodily fluids exhibit a high abundance of other interfering biomolecules. Additionally, target mutations or differences in biomarker expression among various lung cancer subtypes may contribute to detection failures. In this study, we propose a targeted nanoarray-based early cancer diagnostic approach for multiple subtypes of lung cancer. The targeted nanoarray was constructed by modifying five targeting aptamers onto mesoporous silica nanoparticles through the conjugation between amino and carboxyl groups. The flow cytometry experiments demonstrated the specific recognition ability of the targeted nanoarray to tumor exosomes in PBS, even at biomarker expression levels as low as 1.5%. Moreover, the TEM results indicated that the targeted nanoarray could isolate tumor exosomes in the blood of tumor-bearing mice. Furthermore, the targeted nanoarray could detect tumor exosomes in the blood of various lung cancer bearing mice, including at the early stages of cancer, which has just been established for 7 days. Overall, the targeted nanoarray represents a promising tool for the early detection of various subtypes of lung cancer.

Challenges in the management of operable triple-negative breast cancer in a survivor of the B-cell acute lymphoblastic leukemia: a case report

BackgroundOperable triple-negative breast cancer (TNBC) is an unfavorable subtype of breast cancer, which usually requires an aggressive perioperative systemic treatment. When TNBC presents as a second primary cancer after cured acute leukemia, its management might be challenging.Case presentationWe present a case report of a young postmenopausal woman with an operable TNBC who had a history of the B-cell acute lymphoblastic leukemia (B-ALL) and graft versus host disease (GVHD) after allogeneic stem cell transplantation (allo-SCT). A history of previous treatment with anthracyclines and radiotherapy and GVHD limited the use of doxorubicin for treatment of her TNBC. Due to the history of GVHD, perioperative treatment with pembrolizumab was omitted. Genetic testing was challenging due to the possible contamination of her tissues with the donor’s cells after allo-SCT. In samples of our patient’s buccal swab, peripheral blood, and tumor tissue, a pathogenic variant in the partner and localizer of BRCA2 (PALB2) gene was found. With neoadjuvant chemotherapy which included carboplatin, a pathologic complete response was achieved. Although our patient has a low risk for recurrence of TNBC, her risk for the development of new primary cancers remains substantial.ConclusionThis case highlights challenges in the systemic treatment, genetic testing, and follow-up of patients with operable TNBC and other solid cancers who have a history of acute leukemia.