PURPOSE: Patients with postpartum breast cancer diagnosed after cessation of breastfeeding (postweaning, PP-BCPW) have a particularly poor prognosis compared with patients diagnosed during lactation (PP-BCDL), or to pregnant (Pr-BC) and nulliparous (NP-BC) patients, regardless of standard prognostic characteristics. Animal studies point to a role of the involution process in stimulation of tumor growth in the mammary gland. However, in women, the molecular mechanisms that underlie this poor prognosis of patients with PP-BCPW remain vastly underexplored, due to of lack of adequate patient numbers and outcome data. EXPERIMENTAL DESIGN: We explored whether distinct prognostic features, common to all breast cancer molecular subtypes, exist in postpartum tumor tissue. Using detailed breastfeeding data, we delineated the postweaning period in PP-BC as a surrogate for mammary gland involution and performed whole transcriptome sequencing, immunohistochemical, and (multiplex) immunofluorescent analyses on tumor tissue of patients with PP-BCPW, PP-BCDL, Pr-BC, and NP-BC. RESULTS: We found that patients with PP-BCPW having a low expression level of an immunoglobulin gene signature, but high infiltration of plasma B cells, have an increased risk for metastasis and death. Although PP-BCPW tumor tissue was also characterized by an increase in CD8+ cytotoxic T cells and reduced distance among these cell types, these parameters were not associated with differential clinical outcomes among groups. CONCLUSIONS: These data point to the importance of plasma B cells in the postweaning mammary tumor microenvironment regarding the poor prognosis of PP-BCPW patients. Future prospective and in-depth research needs to further explore the role of B-cell immunobiology in this specific group of young patients with breast cancer.

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Background and Objectives: In patients with rectal cancer who received neoadjuvant (chemo)radiotherapy, fibrosis is induced in and around the tumor area. As tumors and fibrosis have similar visual and tactile feedback, they are hard to distinguish during surgery. To prevent positive resection margins during surgery and spare healthy tissue, it would be of great benefit to have a real-time tissue classification technology that can be used in vivo. Study Design/Materials and Methods: In this study diffuse reflectance spectroscopy (DRS) was evaluated for real-time tissue classification of tumor and fibrosis. DRS spectra of fibrosis and tumor were obtained on excised rectal specimens. After normalization using the area under the curve, a support vector machine was trained using a 10-fold cross-validation. Results: Using spectra of pure tumor tissue and pure fibrosis tissue, we obtained a mean accuracy of 0.88. This decreased to a mean accuracy of 0.61 when tumor measurements were used in which a layer of healthy tissue, mainly fibrosis, was present between the tumor and the measurement surface. Conclusion: It is possible to distinguish pure fibrosis from pure tumor. However, when the measurements on tumor also involve fibrotic tissue, the classification accuracy decreases. Lasers Surg. Med.

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Chromatin immunoprecipitation (ChIP)-seq analyses of transcription factors in clinical specimens are challenging due to the technical limitations and low quantities of starting material, often resulting in low enrichments and poor signal-to-noise ratio. Here, we present an optimized protocol for transcription factor ChIP-seq analyses in human tissue, yielding an ~100% success rate for all transcription factors analyzed. As proof of concept and to illustrate general applicability of the approach, human tissue from the breast, prostate, and endometrial cancers were analyzed. In addition to standard formaldehyde fixation, disuccinimidyl glutarate was included in the procedure, greatly increasing data quality. To illustrate the sensitivity of the optimized protocol, we provide high-quality ChIP-seq data for three independent factors (AR, FOXA1, and H3K27ac) from a single core needle prostate cancer biopsy specimen. In summary, double-cross-linking strongly improved transcription factor ChIP-seq quality on human tumor samples, further facilitating and enhancing translational research on limited amounts of tissue.

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Neoadjuvant radiotherapy, as part of the conventional treatment of rectal cancer, can induce fibrotic tissue formation around the tumor. This complicates the exact determination of the tumor borders during surgery, which might increase the chance of positive resection margins. In a previous ex vivo study, we distinguished tumor tissue from healthy rectal wall and fat with an accuracy of 0.95, using diffuse reflectance spectroscopy (DRS). Since this study did not include fibrosis, the aim of the current ex vivo study was to examine whether differentiation of tumor and fibrosis with DRS is possible. DRS measurements from freshly resected specimen of 16 patients were obtained. In eight patients fibrosis was measured, in the other eight patients tumor was measured. The measurements were performed using a DRS probe with a source-detector distance of 2 mm. The spectra were obtained in the wavelength range of 450-1600 nm. Classification of the measurements was done using a support vector machine (SVM) and a set of features extracted from the spectra. The SVM was evaluated using an eight-fold cross-validation, which was repeated ten times. For all repetitions, the area under the ROC curve was greater than 0.85 (mean = 0.87, STD = 0.02). The mean sensitivity and specificity were 0.85 (STD = 0.03) and 0.88 (STD = 0.01) respectively. It can be concluded that tumor tissue can be distinguished from fibrosis based on spectral features from DRS measurements. The next step will be to conduct an in vivo study, to verify these results during surgery.@en

Background: In colorectal cancer surgery there is a delicate balance between complete removal of the tumor and sparing as much healthy tissue as possible. Especially in rectal cancer, intraoperative tissue recognition could be of great benefit in preventing positive resection margins and sparing as much healthy tissue as possible. To better guide the surgeon, we evaluated the accuracy of diffuse reflectance spectroscopy (DRS) for tissue characterization during colorectal cancer surgery and determined the added value of DRS when compared to clinical judgement. Methods: DRS spectra were obtained from fat, healthy colorectal wall and tumor tissue during colorectal cancer surgery and results were compared to histopathology examination of the measurement locations. All spectra were first normalized at 800 nm, thereafter two support vector machines (SVM) were trained using a tenfold cross-validation. With the first SVM fat was separated from healthy colorectal wall and tumor tissue, the second SVM distinguished healthy colorectal wall from tumor tissue. Results: Patients were included based on preoperative imaging, indicating advanced local stage colorectal cancer. Based on the measurement results of 32 patients, the classification resulted in a mean accuracy for fat, healthy colorectal wall and tumor of 0.92, 0.89 and 0.95 respectively. If the classification threshold was adjusted such that no false negatives were allowed, the percentage of false positive measurement locations by DRS was 25% compared to 69% by clinical judgement. Conclusion: This study shows the potential of DRS for the use of tissue classification during colorectal cancer surgery. Especially the low false positive rate obtained for a false negative rate of zero shows the added value for the surgeons. Trail registration This trail was performed under approval from the internal review board committee (Dutch Trail Register NTR5315), registered on 04/13/2015, https://www.trialregister.nl/trial/5175.

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Background: Breast cancer surgeons struggle with differentiating healthy tissue from cancer at the resection margin during surgery. We report on the feasibility of using diffuse reflectance spectroscopy (DRS) for real-time in vivo tissue characterization. Methods: Evaluating feasibility of the technology requires a setting in which measurements, imaging and pathology have the best possible correlation. For this purpose an optical biopsy needle was used that had integrated optical fibers at the tip of the needle. This approach enabled the best possible correlation between optical measurement volume and tissue histology. With this optical biopsy needle we acquired real-time DRS data of normal tissue and tumor tissue in 27 patients that underwent an ultrasound guided breast biopsy procedure. Five additional patients were measured in continuous mode in which we obtained DRS measurements along the entire biopsy needle trajectory. We developed and compared three different support vector machine based classification models to classify the DRS measurements. Results: With DRS malignant tissue could be discriminated from healthy tissue. The classification model that was based on eight selected wavelengths had the highest accuracy and Matthews Correlation Coefficient (MCC) of 0.93 and 0.87, respectively. In three patients that were measured in continuous mode and had malignant tissue in their biopsy specimen, a clear transition was seen in the classified DRS measurements going from healthy tissue to tumor tissue. This transition was not seen in the other two continuously measured patients that had benign tissue in their biopsy specimen. Conclusions: It was concluded that DRS is feasible for integration in a surgical tool that could assist the breast surgeon in detecting positive resection margins during breast surgery. Trail registration NIH US National Library of Medicine-clinicaltrails.gov, NCT01730365. Registered: 10/04/2012 https://clinicaltrials.gov/ct2/show/study/NCT01730365

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Background and Objective: Over the last decade, an increasing effort has been put towards the implementation of optical guidance techniques to aid surgeons during cancer surgery. Diffuse reflectance spectroscopy (DRS) and fluorescence spectroscopy (FS) are two of these new techniques. The objective of this study is to investigate whether in vivo optical spectroscopy is able to accurately discriminate colorectal liver metastases (CRLM) from normal liver tissue in vivo. Materials and Methods: DRS and FS were incorporated at the tip of a needle and were used for in vivo tissue differentiation during resection of CRLM. Measurements were taken in and around the tumor lesions and measurement sites were marked and correlated to histology (i.e., normal liver tissue or tumor tissue). Patients with and without neoadjuvant systemic chemotherapy were included into the study. Results: Four hundred and eighty-four measurements were taken in and near 19 liver lesions prior to resection. Overall sensitivity and specificity for DRS was 95% and 92%, respectively. Bile was the most discriminative parameter. The addition of FS did not improve the overall accuracy. Sensitivity and specificity was not hampered by neo-adjuvant chemotherapy; sensitivity and specificity after neo-adjuvant chemotherapy were 92% and 100%, respectively. Conclusion: We have successfully integrated spectroscopy technology into a disposable 15 Gauge optical needle and we have shown that DRS and FS can accurately discriminate CRLM from normal liver tissue in the in vivo setting regardless of whether the patient was pre-treated with systemic therapy. This technique makes in vivo guidance accessible for common surgical practice. Lasers Surg. Med. 48:820–827, 2016.

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