Mammographic features at primary breast cancer diagnosis in relation to recurrence-free survival.

PURPOSE: The number of women living with breast cancer (BC) is increasing, and the efficacy of surveillance programs after BC treatment is essential. Identification of links between mammographic features and recurrence could help design follow up strategies, which may lead to earlier detection of recurrence. The aim of this study was to analyze associations between mammographic features at diagnosis and their potential association with recurrence-free survival (RFS). METHODS: Women with invasive BC in the prospective Malmö Diet and Cancer Study (n = 1116, 1991-2014) were assessed for locoregional and distant recurrences, with a median follow-up of 10.15 years. Of these, 34 women were excluded due to metastatic disease at diagnosis or missing recurrence data. Mammographic features (breast density [BI-RADS and clinical routine], tumor appearance, mode of detection) and tumor characteristics (tumor size, axillary lymph node involvement, histological grade) at diagnosis were registered. Associations were analyzed using Cox regression, yielding hazard ratios (HR) with 95 % confidence intervals (CI). RESULTS: Of the 1082 women, 265 (24.4 %) had recurrent disease. There was an association between high mammographic breast density at diagnosis and impaired RFS (adjusted HR 1.32 (0.98-1.79). In analyses limited to screen-detected BC, this association was stronger (adjusted HR 2.12 (1.35-3.32). There was no association between mammographic tumor appearance and recurrence. CONCLUSION: RFS was impaired in women with high breast density compared to those with low density, especially among women with screen-detected BC. This study may lead to insights on mammographic features preceding BC recurrence, which could be used to tailor follow up strategies.

Artificial intelligence-supported screen reading versus standard double reading in the Mammography Screening with Artificial Intelligence trial (MASAI): a clinical safety analysis of a randomised, controlled, non-inferiority, single-blinded, screening accuracy study.

BACKGROUND: Retrospective studies have shown promising results using artificial intelligence (AI) to improve mammography screening accuracy and reduce screen-reading workload; however, to our knowledge, a randomised trial has not yet been conducted. We aimed to assess the clinical safety of an AI-supported screen-reading protocol compared with standard screen reading by radiologists following mammography. METHODS: In this randomised, controlled, population-based trial, women aged 40-80 years eligible for mammography screening (including general screening with 1·5-2-year intervals and annual screening for those with moderate hereditary risk of breast cancer or a history of breast cancer) at four screening sites in Sweden were informed about the study as part of the screening invitation. Those who did not opt out were randomly allocated (1:1) to AI-supported screening (intervention group) or standard double reading without AI (control group). Screening examinations were automatically randomised by the Picture Archive and Communications System with a pseudo-random number generator after image acquisition. The participants and the radiographers acquiring the screening examinations, but not the radiologists reading the screening examinations, were masked to study group allocation. The AI system (Transpara version 1.7.0) provided an examination-based malignancy risk score on a 10-level scale that was used to triage screening examinations to single reading (score 1-9) or double reading (score 10), with AI risk scores (for all examinations) and computer-aided detection marks (for examinations with risk score 8-10) available to the radiologists doing the screen reading. Here we report the prespecified clinical safety analysis, to be done after 80 000 women were enrolled, to assess the secondary outcome measures of early screening performance (cancer detection rate, recall rate, false positive rate, positive predictive value [PPV] of recall, and type of cancer detected [invasive or in situ]) and screen-reading workload. Analyses were done in the modified intention-to-treat population (ie, all women randomly assigned to a group with one complete screening examination, excluding women recalled due to enlarged lymph nodes diagnosed with lymphoma). The lowest acceptable limit for safety in the intervention group was a cancer detection rate of more than 3 per 1000 participants screened. The trial is registered with ClinicalTrials.gov, NCT04838756, and is closed to accrual; follow-up is ongoing to assess the primary endpoint of the trial, interval cancer rate. FINDINGS: Between April 12, 2021, and July 28, 2022, 80 033 women were randomly assigned to AI-supported screening (n=40 003) or double reading without AI (n=40 030). 13 women were excluded from the analysis. The median age was 54·0 years (IQR 46·7-63·9). Race and ethnicity data were not collected. AI-supported screening among 39 996 participants resulted in 244 screen-detected cancers, 861 recalls, and a total of 46 345 screen readings. Standard screening among 40 024 participants resulted in 203 screen-detected cancers, 817 recalls, and a total of 83 231 screen readings. Cancer detection rates were 6·1 (95% CI 5·4-6·9) per 1000 screened participants in the intervention group, above the lowest acceptable limit for safety, and 5·1 (4·4-5·8) per 1000 in the control group-a ratio of 1·2 (95% CI 1·0-1·5; p=0·052). Recall rates were 2·2% (95% CI 2·0-2·3) in the intervention group and 2·0% (1·9-2·2) in the control group. The false positive rate was 1·5% (95% CI 1·4-1·7) in both groups. The PPV of recall was 28·3% (95% CI 25·3-31·5) in the intervention group and 24·8% (21·9-28·0) in the control group. In the intervention group, 184 (75%) of 244 cancers detected were invasive and 60 (25%) were in situ; in the control group, 165 (81%) of 203 cancers were invasive and 38 (19%) were in situ. The screen-reading workload was reduced by 44·3% using AI. INTERPRETATION: AI-supported mammography screening resulted in a similar cancer detection rate compared with standard double reading, with a substantially lower screen-reading workload, indicating that the use of AI in mammography screening is safe. The trial was thus not halted and the primary endpoint of interval cancer rate will be assessed in 100 000 enrolled participants after 2-years of follow up. FUNDING: Swedish Cancer Society, Confederation of Regional Cancer Centres, and the Swedish governmental funding for clinical research (ALF).

Investigating the prognostic value of mammographic breast density and mammographic tumor appearance in women with invasive breast cancer: The Malmö Diet and cancer study.

BACKGROUND: High breast density is a risk factor for breast cancer. However, whether density is a prognostic factor is debatable. Also, tumor appearances are related to tumor characteristics. Here we investigate the relationship between breast cancer-specific survival and mammographic breast density and mammographic tumor appearances. METHODS: Women in the Malmö Diet and Cancer study with invasive breast cancer 1991-2014 were included (n = 1116). Mammographic information, patient and tumor characteristics, vital status, and causes of death were collected through 2018. Breast cancer-specific survival was assessed with Kaplan-Meier estimates and Cox proportional hazard models. Analyses were adjusted for established prognostic factors and stratified by detection mode. RESULTS: High breast density did not significantly impact breast cancer-specific survival. However, there may be increased risk in women with dense breasts and screening-detected tumors (HR 1.45, CI 0.87-2.43). Neither did tumor appearance impact breast cancer-specific survival at long-term follow-up. CONCLUSIONS: Breast cancer prognosis in women with high breast density on mammography does not seem impaired compared to women with less dense breasts, once the cancer is established. Neither does mammographic tumor appearance seem to inflict on prognosis, findings that can be of value in the management of breast cancer.

Mammographic density in relation to breast cancer recurrence and survival in women receiving neoadjuvant chemotherapy.

Objective: The association between mammographic density (MD) and breast cancer (BC) recurrence and survival remains unclear. Patients receiving neoadjuvant chemotherapy (NACT) are in a vulnerable situation with the tumor within the breast during treatment. This study evaluated the association between MD and recurrence/survival in BC patients treated with NACT. Methods: Patients with BC treated with NACT in Sweden (2005-2016) were retrospectively included (N=302). Associations between MD (Breast Imaging-Reporting and Data System (BI-RADS) 5th Edition) and recurrence-free/BC-specific survival at follow-up (Q1 2022) were addressed. Hazard ratios (HRs) for recurrence/BC-specific survival (BI-RADS a/b/c vs. d) were estimated using Cox regression analysis and adjusted for age, estrogen receptor status, human epidermal growth factor receptor 2 status, axillary lymph node status, tumor size, and complete pathological response. Results: A total of 86 recurrences and 64 deaths were recorded. The adjusted models showed that patients with BI-RADS d vs. BI-RADS a/b/c had an increased risk of recurrence (HR 1.96 (95% confidence interval (CI) 0.98-3.92)) and an increased risk of BC-specific death (HR 2.94 (95% CI 1.43-6.06)). Conclusion: These findings raise questions regarding personalized follow-up for BC patients with extremely dense breasts (BI-RADS d) pre-NACT. More extensive studies are required to confirm our findings.

Radiologically enlarged cardiophrenic lymph nodes and CA-125 in relation to diaphragmatic carcinomatosis, surgical outcome, and overall survival in advanced ovarian cancer.

BACKGROUND: We primarily aimed to determine whether the presence of enlarged cardiophrenic lymph nodes (CPLNs), visualized by computed tomography (CT), and CA-125 can be used to assess diaphragmatic carcinomatosis and residual disease (RD) in advanced ovarian cancer (AOC) patients treated with upfront surgery. The secondary aim was to determine the prognostic role of CT-CPLNs in overall survival (OS). MATERIAL AND METHODS: A single-center, retrospective, population-based study was conducted of patients who underwent surgery for AOC from January 1, 2014-December 31, 2018. Suspicious CT-CPLNs were defined as having a short axis ≥5 mm. The median survival and rate of survival were calculated with the Kaplan-Meier method using multivariate Cox regression analyses, including comparisons of complete cytoreductive surgery (CCS; defined as the complete removal of all intra-abdominal tumor) versus noncomplete cytoreductive surgery (non-CCS) and analyses related to CT-CPLN status and preoperative CA-125 values. RESULTS: We included 208 patients. CT-CPLNs correlated with both diaphragmatic carcinomatosis (OR 3.59, 95% CI 1.81-7.16, p < 0.01) and RD (OR 2.54, 95% CI 1.38-4.6, p = 0.003). When CCS was achieved, no differences in survival between patients with suspicious or nonsuspicious CT-CPLNs were found. The relationships between CA-125 ≥ 500 U/ml and diaphragmatic carcinomatosis (OR 3.51, 95% CI 1.86-6.64, p < 0.01) and RD (OR 2.41, 95% CI 1.33-4.38, p = 0.004) were positive. All data were adjusted for age and ECOG performance status. Survival analyses were also adjusted for RD. CONCLUSION: Enlarged CPLNs on CT scans and CA-125 levels correlate with diaphragmatic carcinomatosis and RD at the end of the surgery. The strongest prognostic factor for OS remains CCS, regardless of the CT-CPLN status.

Imaging ovarian cancer - from baseline characteristics to high-risk image factors.

BACKGROUND: Imaging ovarian cancer (OC) includes evaluating peritoneal carcinomatosis (PC) and enlarged cardio phrenic lymph nodes (CPLN) by computed tomography (CT), and thorough evaluation is tedious work. A "CT short score" with high-risk CT parameters might be a more pragmatic approach, but it is not known if such a short score associates with aggressive OC subtypes and impaired OC survival. Further, it is not known if certain established OC risk factors are linked to high-risk CT-findings which would be important in image evaluation. Herein, we investigate a CT short score and its relation to baseline characteristics, OC subtypes, and survival. METHODS: The Malmö Diet and Cancer Study is a prospective cohort that included 17,035 women (1991-1996). Baseline characteristics and tumor information on 159 OC and information on OC specific survival (last follow-up, 2017-12-31) was registered. A CT short score (CPLN and PC-index (PCI) in seven regions) was registered and associations with clinical stage [stage I vs. advanced stage (II-IV), histological type/grade (high grade serous and endometrioid vs. other subtypes], and OC-specific survival were analyzed with logistic and Cox regression, respectively. Parity and menopausal status were analyzed in relation to short score and PCI. RESULTS: There was an association between higher short score and advanced clinical stage (adjusted OR 2.76 (1.42-5.38)), adjusted for age at diagnosis and histological type/grade. Higher short score was associated with impaired OC specific survival (adjusted HR 1.17 (1.01-1.35)), adjusted for age at diagnosis, histological type/grade, and clinical stage. There were no significant associations between parity, menopausal status, and short score/PCI. CONCLUSIONS: CT short score was significantly associated with advanced clinical stages and impaired OC survival. A pragmatic approach (based on CT) to evaluate high risk image findings in OC could help reduce radiologists' workload and at the same time provide structured reports to surgeons and oncologists involved in OC care.

An immune score reflecting pro- and anti-tumoural balance of tumour microenvironment has major prognostic impact and predicts immunotherapy response in solid cancers.

BACKGROUND: Cancer immunity is based on the interaction of a multitude of cells in the spatial context of the tumour tissue. Clinically relevant immune signatures are therefore anticipated to fundamentally improve the accuracy in predicting disease progression. METHODS: Through a multiplex in situ analysis we evaluated 15 immune cell classes in 1481 tumour samples. Single-cell and bulk RNAseq data sets were used for functional analysis and validation of prognostic and predictive associations. FINDINGS: By combining the prognostic information of anti-tumoural CD8+ lymphocytes and tumour supportive CD68+CD163+ macrophages in colorectal cancer we generated a signature of immune activation (SIA). The prognostic impact of SIA was independent of conventional parameters and comparable with the state-of-art immune score. The SIA was also associated with patient survival in oesophageal adenocarcinoma, bladder cancer, lung adenocarcinoma and melanoma, but not in endometrial, ovarian and squamous cell lung carcinoma. We identified CD68+CD163+ macrophages as the major producers of complement C1q, which could serve as a surrogate marker of this macrophage subset. Consequently, the RNA-based version of SIA (ratio of CD8A to C1QA) was predictive for survival in independent RNAseq data sets from these six cancer types. Finally, the CD8A/C1QA mRNA ratio was also predictive for the response to checkpoint inhibitor therapy. INTERPRETATION: Our findings extend current concepts to procure prognostic information from the tumour immune microenvironment and provide an immune activation signature with high clinical potential in common human cancer types. FUNDING: Swedish Cancer Society, Lions Cancer Foundation, Selanders Foundation, P.O. Zetterling Foundation, U-CAN supported by SRA CancerUU, Uppsala University and Region Uppsala.

Metabolic parameters of [18F]FDG PET-CT before and after radiotherapy may predict survival and recurrence in cervical cancer.

BACKGROUND: Cervical cancer is the fourth most common female malignancy. [18F]-fluorodeoxyglucose (FDG) positron emission tomography with computed tomography (PET-CT) is routinely performed in patients with locally advanced cervical cancer for staging and treatment response evaluation. With this retrospective, observational cohort study, we wanted to investigate the prognostic value of the maximum standardised uptake value (SUVmax) and the volumetric parameters of metabolic tumour volume (MTV) and total lesion glycolysis (TLG) before and after treatment in women with cervical cancer, with overall survival (OS) and recurrence as outcome measures. METHODS: Women with cervical cancer referred for curative radiotherapy and who underwent two PET-CT scans (before treatment and approximately 7 months post-treatment) were included. SUVmax, MTV and TLG were measured at baseline and post-treatment on the primary tumour, pelvic and distant lymph node metastases, distant organ metastases, and on total tumour burden. The PET parameters were associated with OS by Cox regression and recurrence by multivariable logistic regression. Kaplan-Meier curves and C-index were used to visualise the prognostic potential of the different measures. RESULTS: A total of 133 patients were included. At the primary tumour level and on total tumour burden, age- and clinical-stage adjusted analyses showed a significant association between PET parameters and OS and recurrence when measured post-treatment. At baseline (pre-treatment), MTV and TLG were associated with OS and recurrence, whereas SUVmax was not. C-index from adjusted Cox models on total tumour burden showed higher values for the post-treatment PET compared to baseline. Kaplan-Meier curves demonstrated a greater prognostic potential for MTV and TLG compared to SUVmax, both at baseline and post-treatment. CONCLUSIONS: The FDG PET-CT-derived parameters SUVmax, MTV, and TLG measured post-treatment can predict OS and recurrence in cervical cancer. Parameters measured before treatment had overall lower prognostic potential, and only MTV and TLG showed significant association to OS and recurrence.

Metabolically Defined Body Size Phenotypes and Risk of Endometrial Cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC).

BACKGROUND: Obesity is a risk factor for endometrial cancer but whether metabolic dysfunction is associated with endometrial cancer independent of body size is not known. METHODS: The association of metabolically defined body size phenotypes with endometrial cancer risk was investigated in a nested case-control study (817 cases/ 817 controls) within the European Prospective Investigation into Cancer and Nutrition (EPIC). Concentrations of C-peptide were used to define metabolically healthy (MH; <1st tertile) and metabolically unhealthy (MU; ≥1st tertile) status among the control participants. These metabolic health definitions were combined with normal weight (NW); body mass index (BMI)<25 kg/m2 or waist circumference (WC)<80 cm or waist-to-hip ratio (WHR)<0.8) and overweight (OW; BMI≥25 kg/m2 or WC≥80 cm or WHR≥0.8) status, generating four phenotype groups for each anthropometric measure: (i) MH/NW, (ii) MH/OW, (iii) MU/NW, and (iv) MU/OW. RESULTS: In a multivariable-adjusted conditional logistic regression model, compared with MH/NW individuals, endometrial cancer risk was higher among those classified as MU/NW [ORWC, 1.48; 95% confidence interval (CI), 1.05-2.10 and ORWHR, 1.68; 95% CI, 1.21-2.35] and MU/OW (ORBMI, 2.38; 95% CI, 1.73-3.27; ORWC, 2.69; 95% CI, 1.92-3.77 and ORWHR, 1.83; 95% CI, 1.32-2.54). MH/OW individuals were also at increased endometrial cancer risk compared with MH/NW individuals (ORWC, 1.94; 95% CI, 1.24-3.04). CONCLUSIONS: Women with metabolic dysfunction appear to have higher risk of endometrial cancer regardless of their body size. However, OW status raises endometrial cancer risk even among women with lower insulin levels, suggesting that obesity-related pathways are relevant for the development of this cancer beyond insulin. IMPACT: Classifying women by metabolic health may be of greater utility in identifying those at higher risk for endometrial cancer than anthropometry per se.

Prognostic Value of Peritoneal Cancer Index After Complete Cytoreductive Surgery in Advanced Ovarian Cancer.

BACKGROUND/AIM: Residual disease (RD) after primary debulking surgery (PDS) is a prognostic factor for survival in advanced ovarian cancer (AOC). This study aimed to examine whether the tumor extent affects overall survival (OS) and progression-free survival (PFS) in AOC patients treated with PDS. PATIENTS AND METHODS: A total of 118 patients treated with PDS were included. Age, ECOG score, AOC International Federation of Gynecology and Obstetrics (FIGO) stage, CA-125, RD, peritoneal cancer index (PCI), preoperative imaging (CT-PCI) and macroscopic visualization at the surgery start (S-PCI) were analyzed. Tumor extent was quantified using the PCI, and by CT-PCI and S-PCI. Cox regression, Kaplan-Meier and receiver operating curves (ROC) were performed for survival analyses. RESULTS: S-PCI correlated with both OS (1.067, 95%CI=1.018-1.119, p<0.007) and PFS. Patients exhibiting S-PCI≥18.5, adjusted to age, performance status, and RD, had a two-fold risk of dying (HR=2.070, 95%CI=1.061-4.038, p=0.033) compared those with PCI<18.5. CT-PCI correlated with OS in crude data (1.037, 95%CI=1.005-1.071, p=0.025), but this was not sustained in multivariate analyses. RD of any size doubled the risk of dying (2.177, 95%CI=1.235-3.838, p=0.007). CONCLUSION: The tumor extent at the beginning of surgery seemed to affect OS in patients with AOC, regardless of the extent of RD at the end of the surgery. PCI above 18.5 doubled the risk of dying of the disease. No difference in major complications was noted in the two groups of patients. CT-PCI seemed to play a prognostic role for PFS; however, it is still to be investigated as a prognostic factor for OS.

The role of computed tomography in the assessment of tumour extent and the risk of residual disease after upfront surgery in advanced ovarian cancer (AOC).

PURPOSE: Epithelial ovarian cancer is usually diagnosed in the advanced stages. To choose the best therapeutic approach, an accurate preoperative assessment of the tumour extent is crucial. This study aimed to determine whether the peritoneal cancer index (PCI), the amount of ascites, and the presence of cardiophrenic nodes (CPLNs) visualized by computed tomography (CT) can assess the tumour extent (S-PCI) and residual disease (RD) for advanced ovarian cancer (AOC) patients treated with upfront surgery. METHODS: In total, 118 AOC cases were included between January 2016 and December 2018 at Skåne University Hospital, Lund, Sweden. Linear regression and interclass correlation (ICC) analyses were used to determine the relationship between CT-PCI and S-PCI. The patients were stratified in complete cytoreductive surgery (CCS) with no RD or to non-CCS with RD of any size. The amount of ascites on CT (CT-ascites), CA-125 and the presence of radiological enlarged CPLNs (CT-CPLN) were analysed to evaluate their impact on estimating RD. RESULTS: CT-PCI correlated well with S-PCI (0.397; 95% CI 0.252-0.541; p < 0.001). The risk of RD was also related to CT-PCI (OR 1.069 (1.009-1.131), p < 0.023) with a cut-off of 21 for CT-PCI (0.715, p = 0.000). The sensitivity, specificity, positive predictive value and negative predictive value were 58.5, 70.3, 52.2 and 75.4%, respectively. CT-ascites above 1000 ml predicted RD (OR 3.510 (1.298-9.491) p < 0.013). CONCLUSION: CT is a reliable tool to assess the extent of the disease in advanced ovarian cancer. Higher CT-PCI scores and large volumes of ascites estimated on CT predicted RD of any size.

Prospective evaluation of 92 serum protein biomarkers for early detection of ovarian cancer.

BACKGROUND: CA125 is the best available yet insufficiently sensitive biomarker for early detection of ovarian cancer. There is a need to identify novel biomarkers, which individually or in combination with CA125 can achieve adequate sensitivity and specificity for the detection of earlier-stage ovarian cancer. METHODS: In the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we measured serum levels of 92 preselected proteins for 91 women who had blood sampled ≤18 months prior to ovarian cancer diagnosis, and 182 matched controls. We evaluated the discriminatory performance of the proteins as potential early diagnostic biomarkers of ovarian cancer. RESULTS: Nine of the 92 markers; CA125, HE4, FOLR1, KLK11, WISP1, MDK, CXCL13, MSLN and ADAM8 showed an area under the ROC curve (AUC) of ≥0.70 for discriminating between women diagnosed with ovarian cancer and women who remained cancer-free. All, except ADAM8, had shown at least equal discrimination in previous case-control comparisons. The discrimination of the biomarkers, however, was low for the lag-time of >9-18 months and paired combinations of CA125 with any of the 8 markers did not improve discrimination compared to CA125 alone. CONCLUSION: Using pre-diagnostic serum samples, this study identified markers with good discrimination for the lag-time of 0-9 months. However, the discrimination was low in blood samples collected more than 9 months prior to diagnosis, and none of the markers showed major improvement in discrimination when added to CA125.

Polyphenol Intake and Epithelial Ovarian Cancer Risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) Study.

Despite some epidemiological evidence on the protective effects of polyphenol intake on epithelial ovarian cancer (EOC) risk from case-control studies, the evidence is scarce from prospective studies and non-existent for several polyphenol classes. Therefore, we aimed to investigate the associations between the intake of total, classes and subclasses of polyphenols and EOC risk in a large prospective study. The study was conducted in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, which included 309,129 adult women recruited mostly from the general population. Polyphenol intake was assessed through validated country-specific dietary questionnaires and the Phenol-Explorer database. During a mean follow-up of 14 years, 1469 first incident EOC cases (including 806 serous, 129 endometrioid, 102 mucinous, and 67 clear cell tumours) were identified. In multivariable-adjusted Cox regression models, the hazard ratio in the highest quartile of total polyphenol intake compared with the lowest quartile (HRQ4vsQ1) was 1.14 (95% CI 0.94-1.39; p-trend = 0.11). Similarly, the intake of most classes and subclasses of polyphenols were not related to either overall EOC risk or any EOC subtype. A borderline statistically significant positive association was observed between phenolic acid intake (HRQ4vsQ1 = 1.20, 95% CI 1.01-1.43; p-trend = 0.02) and EOC risk, especially for the serous subtype and in women with obesity, although these associations did not exceed the Bonferroni correction threshold. The current results do not support any association between polyphenol intake and EOC in our large European prospective study. Results regarding phenolic acid intake need further investigation.

"Association of mammographic features with molecular breast tumor profiles".

PURPOSE: Mammographic density and tumor appearance are breast cancer prognostic factors. Conceivably, mammographic features are macroscopic reflections of tumor´s molecular composition, but to an unknown extent. Our aim was to study associations of mammographic features with molecular tumor profiles. METHODS: Invasive breast cancers (2007-2016) in Malmö Diet and Cancer Study (MDCS) for which there were tumor RNA-sequencing analyses within Sweden Cancerome Analysis Network - Breast (SCAN-B) (n=102) or All Breast Cancer in Malmö (ABIM) (n=50) were identified. Density (fatty vs. dense), tumor appearance (mass vs. spiculation), and intrinsic subtypes were registered. Differences in gene/metagene expression and Microenvironment Cell Population Counter were analyzed with R. Overall survival was used as endpoint. RESULTS: No gene expression differences between density groups was observed. In one cohort (but not the other), Luminal A tumors associated with fatty breasts. For spiculation vs. mass, (p<0.01, t-test) 86 genes were differentially expressed; only one gene was differentially expressed comparing density. Gene set enrichment analysis showed genes highly expressed in spiculated tumors were enriched for extracellular matrix-associated genes whereas genes highly expressed with masses were associated with proliferation. A spiculation metagene, based on differentially expressed genes, showed association with estrogen receptor positivity, lower grade, and improved survival, but it was not an independent prognostic factor. CONCLUSION: There are clear differences in molecular composition between breast tumors with a spiculated appearance vs. a mass as the dominant tumor appearance. However, there are no apparent molecular differences related to the density of the breast in which the tumor has arisen.

Patterns of pathologic lymph nodes in anal cancer: a PET-CT-based analysis with implications for radiotherapy treatment volumes.

BACKGROUND: This study investigates the patterns of PET-positive lymph nodes (LNs) in anal cancer. The aim was to provide information that could inform future anal cancer radiotherapy contouring guidelines. METHODS: The baseline [18F]-FDG PET-CTs of 190 consecutive anal cancer patients were retrospectively assessed. LNs with a Deauville score (DS) of ≥3 were defined as PET-positive. Each PET-positive LN was allocated to a LN region and a LN sub-region; they were then mapped on a standard anatomy reference CT. The association between primary tumor localization and PET-positive LNs in different regions were analyzed. RESULTS: PET-positive LNs (n = 412) were identified in 103 of 190 patients (54%). Compared to anal canal tumors with extension into the rectum, anal canal tumors with perianal extension more often had inguinal (P < 0.001) and less often perirectal (P < 0.001) and internal iliac (P < 0.001) PET-positive LNs. Forty-two patients had PET-positive LNs confined to a solitary region, corresponding to first echelon nodes. The most common solitary LN region was inguinal (25 of 42; 60%) followed by perirectal (26%), internal iliac (10%), and external iliac (2%). No PET-positive LNs were identified in the ischiorectal fossa or in the inguinal area located posterolateral to deep vessels. Skip metastases above the bottom of the sacroiliac joint were quite rare. Most external iliac PET-positive LNs were located posterior to the external iliac vein; only one was located in the lateral external iliac sub-region. CONCLUSIONS: The results support some specific modifications to the elective clinical target volume (CTV) in anal cancer. These changes would lead to reduced volumes of normal tissue being irradiated, which could contribute to a reduction in radiation side-effects.

Metabolic signatures of greater body size and their associations with risk of colorectal and endometrial cancers in the European Prospective Investigation into Cancer and Nutrition.

BACKGROUND: The mechanisms underlying the obesity-cancer relationship are incompletely understood. This study aimed to characterise metabolic signatures of greater body size and to investigate their association with two obesity-related malignancies, endometrial and colorectal cancers, and with weight loss within the context of an intervention study. METHODS: Targeted mass spectrometry metabolomics data from 4326 participants enrolled in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort and 17 individuals from a single-arm pilot weight loss intervention (Intercept) were used in this analysis. Metabolic signatures of body size were first determined in discovery (N = 3029) and replication (N = 1297) sets among EPIC participants by testing the associations between 129 metabolites and body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) using linear regression models followed by partial least squares analyses. Conditional logistic regression models assessed the associations between the metabolic signatures with endometrial (N = 635 cases and 648 controls) and colorectal (N = 423 cases and 423 controls) cancer risk using nested case-control studies in EPIC. Pearson correlation between changes in the metabolic signatures and weight loss was tested among Intercept participants. RESULTS: After adjustment for multiple comparisons, greater BMI, WC, and WHR were associated with higher levels of valine, isoleucine, glutamate, PC aa C38:3, and PC aa C38:4 and with lower levels of asparagine, glutamine, glycine, serine, lysoPC C17:0, lysoPC C18:1, lysoPC C18:2, PC aa C42:0, PC ae C34:3, PC ae C40:5, and PC ae C42:5. The metabolic signature of BMI (OR1-sd 1.50, 95% CI 1.30-1.74), WC (OR1-sd 1.46, 95% CI 1.27-1.69), and WHR (OR1-sd 1.54, 95% CI 1.33-1.79) were each associated with endometrial cancer risk. Risk of colorectal cancer was positively associated with the metabolic signature of WHR (OR1-sd: 1.26, 95% CI 1.07-1.49). In the Intercept study, a positive correlation was observed between weight loss and changes in the metabolic signatures of BMI (r = 0.5, 95% CI 0.06-0.94, p = 0.03), WC (r = 0.5, 95% CI 0.05-0.94, p = 0.03), and WHR (r = 0.6, 95% CI 0.32-0.87, p = 0.01). CONCLUSIONS: Obesity is associated with a distinct metabolic signature comprising changes in levels of specific amino acids and lipids which is positively associated with both colorectal and endometrial cancer and is potentially reversible following weight loss.

Proteogenomic Workflow Reveals Molecular Phenotypes Related to Breast Cancer Mammographic Appearance.

Proteogenomic approaches have enabled the generat̲ion of novel information levels when compared to single omics studies although burdened by extensive experimental efforts. Here, we improved a data-independent acquisition mass spectrometry proteogenomic workflow to reveal distinct molecular features related to mammographic appearances in breast cancer. Our results reveal splicing processes detectable at the protein level and highlight quantitation and pathway complementarity between RNA and protein data. Furthermore, we confirm previously detected enrichments of molecular pathways associated with estrogen receptor-dependent activity and provide novel evidence of epithelial-to-mesenchymal activity in mammography-detected spiculated tumors. Several transcript-protein pairs displayed radically different abundances depending on the overall clinical properties of the tumor. These results demonstrate that there are differentially regulated protein networks in clinically relevant tumor subgroups, which in turn alter both cancer biology and the abundance of biomarker candidates and drug targets.

The prognostic impact of the tumour stroma fraction: A machine learning-based analysis in 16 human solid tumour types.

BACKGROUND: The development of a reactive tumour stroma is a hallmark of tumour progression and pronounced tumour stroma is generally considered to be associated with clinical aggressiveness. The variability between tumour types regarding stroma fraction, and its prognosis associations, have not been systematically analysed. METHODS: Using an objective machine-learning method we quantified the tumour stroma in 16 solid cancer types from 2732 patients, representing retrospective tissue collections of surgically resected primary tumours. Image analysis performed tissue segmentation into stromal and epithelial compartment based on pan-cytokeratin staining and autofluorescence patterns. FINDINGS: The stroma fraction was highly variable within and across the tumour types, with kidney cancer showing the lowest and pancreato-biliary type periampullary cancer showing the highest stroma proportion (median 19% and 73% respectively). Adjusted Cox regression models revealed both positive (pancreato-biliary type periampullary cancer and oestrogen negative breast cancer, HR(95%CI)=0.56(0.34-0.92) and HR(95%CI)=0.41(0.17-0.98) respectively) and negative (intestinal type periampullary cancer, HR(95%CI)=3.59(1.49-8.62)) associations of the tumour stroma fraction with survival. INTERPRETATION: Our study provides an objective quantification of the tumour stroma fraction across major types of solid cancer. Findings strongly argue against the commonly promoted view of a general associations between high stroma abundance and poor prognosis. The results also suggest that full exploitation of the prognostic potential of tumour stroma requires analyses that go beyond determination of stroma abundance. FUNDING: The Swedish Cancer Society, The Lions Cancer Foundation Uppsala, The Swedish Government Grant for Clinical Research, The Mrs Berta Kamprad Foundation, Sweden, Sellanders foundation, P.O.Zetterling Foundation, and The Sjöberg Foundation, Sweden.

Mammographic density as an image-based biomarker of therapy response in neoadjuvant-treated breast cancer patients.

PURPOSE: Personalized cancer treatment requires predictive biomarkers, including image-based biomarkers. Breast cancer (BC) patients receiving neoadjuvant chemotherapy (NACT) are in a clinically vulnerable situation with the tumor present. This study investigated whether mammographic density (MD), assessed pre-NACT, is predictive of pathological complete response (pCR). METHODS: A total of 495 BC patients receiving NACT in Sweden 2005-2019 were included, merged from two different cohorts. Cohort 1 was retrospectively collected (n = 295) and cohort 2 was prospectively collected (n = 200). Mammograms were scored for MD pre-NACT according to the Breast Imaging-Reporting and Data System (BI-RADS), 5th Edition. The association between MD and accomplishing pCR post-NACT was analyzed using logistic regression models-for the whole cohort, stratified by menopausal status, and in different St. Gallen surrogate subtypes. RESULTS: In comparison to patients with low MD (BI-RADS a), the multivariable-adjusted odds ratio (OR) of accomplishing pCR following NACT was on a descending scale: 0.62 (95% confidence interval (CI) 0.24-1.57), 0.38 (95% CI 0.14-1.02), and 0.32 (95% CI 0.09-1.08) for BI-RADS b, c, and d, respectively. For premenopausal patients selectively, the corresponding point estimates were lower, although wider CIs: 0.31 (95% CI 0.06-1.62), 0.24 (95% CI 0.04-1.27), and 0.13 (95% CI 0.02-0.88). Subgroup analyses based on BC subtypes resulted in imprecise estimates, i.e., wide CIs. CONCLUSIONS: It seemed as though patients with higher MD at baseline were less likely to reach pCR after NACT-a finding more pronounced in premenopausal women. Larger multicenter studies are needed to enable analyses and interpretation for different BC subtypes.

Mammographic tumour appearance is related to clinicopathological factors and surrogate molecular breast cancer subtype.

Mammographic tumour appearance may provide prognostic useful information. For example, spiculation indicates invasiveness, but also better survival compared to tumours with other appearances. We aimed to study the relationship between mammographic tumour appearance and established clinicopathological factors, including surrogate molecular breast cancer subtypes, in the large Malmö Diet and Cancer Study. A total of 1116 women with invasive breast cancer, diagnosed between 1991 and 2014, were included. Mammographic tumour appearance in relation to status for oestrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2, histological grade, Ki67 and molecular subtype was analysed using various regression models. All models were adjusted for relevant confounders, including breast density, which can affect mammographic appearance. The results consistently showed that spiculated tumours are indicative of favourable characteristics, as they are more likely to be ER and PR positive, and more often exhibit lower histological grade and lower Ki67 expression. Furthermore, spiculated tumours tend to be of luminal A-like subtype, which is associated with a good prognosis. The establishment of associations between mammographic tumour appearance and clinico-pathological factors may aid in characterizing breast cancer at an earlier stage. This could contribute to more individualized breast cancer treatment in the future.