MEK1/2 inhibition in KPC KrasG12D/fl mice with established tumours reverses enrichment of immune response related gene programmes.

Release from AZD6244 treatment results in rapid acinar to ductal metaplasia in KC KrasG12D/fl.

Acceleration of pancreatic tumour initiation after loss of wild-type Kras in KPC KrasG12D/fl mice.

Loss of wild-type KRAS does not alter PI3K-AKT signalling.

Loss of wild-type KRAS sensitizes KPC KrasG12D/fl tumours to MEK1/2 inhibition.

Late-stage intervention with MEK1/2 inhibition improves survival of KPC KrasG12D/fl mice. A, Experimental schematic. KPC KrasG12D/+ and KPC KrasG12D/fl mice were palpated for tumor burden, with palpable tumor burden confirmed by ultrasound imaging, with mice treated continuously from the following day with either vehicle or AZD6244. Tumor growth was monitored by ultrasound imaging once weekly to clinical endpoint. B, Relative volume of pancreatic tumors arising in KPC KrasG12D/+ and KPC KrasG12D/fl mice treated with either vehicle control or AZD6244 from palpable tumor and aged to clinical endpoint. Tumor volume was measured once weekly by high-resolution ultrasound imaging. Each line represents an individual mouse of the indicated genotype and treatment. KPC KrasG12D/fl vehicle, n = 6; KPC KrasG12D/fl AZD6244, n = 7; KPC KrasG12D/+ vehicle, n = 6; KPC KrasG12D/+ AZD6244, n = 4. FC, fold change. C, Change of tumor volume (mm3) of KPC KrasG12D/+ and KPC KrasG12D/fl mice treated with either vehicle control or AZD6244 from palpable tumor between initial ultrasound measurement and a secondary ultrasound measurement (between 6 and 13 days later). Plot represents Log2(FC) of tumor volume between first and second measurements for the full treatment cohort when more than one imaging session was possible. KPC KrasG12D/fl vehicle, n = 5; KPC KrasG12D/fl AZD6244, n = 7; KPC KrasG12D/+ vehicle, n = 4; KPC KrasG12D/+ AZD6244, n = 4. D, Kaplan–Meier survival curves for KPC KrasG12D/+ and KPC KrasG12D/fl mice treated with vehicle or AZD6244, as indicated, from palpable tumor burden and aged to clinical endpoint. KPC KrasG12D/fl vehicle, n = 5; KPC KrasG12D/fl AZD6244, n = 8; KPC KrasG12D/+ vehicle, n = 6; KPC KrasG12D/+ AZD6244, n = 5. MS, median survival. E, Representative hematoxylin and eosin images of tumors from KPC KrasG12D/+ and KPC KrasG12D/fl mice treated with vehicle or AZD6244, as indicated, from palpable tumor burden and aged until clinical endpoint. Representative of five mice per group. Scale bar, 500 μm. F, Left, volcano plot for differentially expressed genes of KPC KrasG12D/+ tumors treated with vehicle or AZD6244 from palpable tumor burden to clinical endpoint. Right, volcano plot for differentially expressed genes of KPC KrasG12D/fl tumors treated with vehicle or AZD6244 from palpable tumor burden to clinical endpoint. Red, significantly altered genes. G, Schematic representing relative impact of WT Kras deletion upon tumur outgrowth and therapeutic responses from KPC KrasG12D/+ and KrasG12D/fl comparison.

We aim to review the current medical and surgical management strategies for lymphedema and present methods for their successful integration into clinical practice. In addition, the following summary background data is provided. Lymphedema is a chronic condition resulting from impaired lymphatic drainage, leading to significant morbidity and reduced quality of life. Traditional management includes conservative therapies such as compression garments and physical therapy. However, advancements in surgical techniques have opened new avenues for treatment. This review aims to synthesize the available literature on both medical and surgical approaches to lymphedema management. This article explores the senior author’s strategies and experiences in lymphedema treatment, supplemented by a literature review that supports the described techniques. Effective lymphedema management is multifaceted, necessitating accurate diagnosis, medical treatment, and in some cases, surgical intervention. The senior author has sought to streamline his approach to this complex condition, and this article outlines his algorithm and techniques for treatment. While conservative treatments remain the foundation of lymphedema management, surgical options in the properly selected patients have shown promising results. The integration of these approaches could enhance overall treatment efficacy and improve quality of life for individuals affected by lymphedema.

Loss of WT Kras increases PanIN formation in the presence of oncogenic Kras. A, Kaplan–Meier survival curve for human patients with PDAC with KRAS alleles balanced and KRAS alleles imbalanced. KRAS balanced, n = 47; KRAS imbalanced, n = 32. *, P = 0.029, log-rank (Mantel–Cox) test. B, Proportion of human patients with pancreatic cancer with KRAS alleles balanced (59.5%) and KRAS alleles imbalanced (40.5%), from A. C, Schematic representing generation of KC KrasG12D/fl mice. D, Representative hematoxylin and eosin (H&E) images of pancreata from KC KrasG12D/+ and KC KrasG12D/fl mice at 42 days of age, representative of six mice per group. Scale bar, 200 μm. E, Quantification and grading of PanINs from KC KrasG12D/+ and KC KrasG12D/fl mice at 42 days of age from one whole hematoxylin and eosin section per mouse (n = 6 per group), represented by D. Boxes depict the IQR, the central line indicates the median, and whiskers indicate minimum/maximum values. **, P < 0.01; one-way Mann–Whitney U test. F, Quantification of the area of ADM per mm2 pancreas over one whole hematoxylin and eosin section from KC KrasG12D/+ and KC KrasG12D/fl mice at 42 days of age (n = 6 per group). Boxes depict the IQR, the central line indicates the median, and whiskers indicate minimum/maximum values. **, P < 0.0011; one-way Mann–Whitney U test. G, Left, representative IHC images of pERK1/2 of pancreata from KC KrasG12D/+ and KC KrasG12D/fl mice at 42 days of age. Representative of six mice per group. Scale bar, 200 μm. Right, bar graphs showing quantification of pERK1/2-positive cells of the pancreatic epithelium of KC KrasG12D/+ and KC KrasG12D/fl mice sampled at day 42 (KC KrasG12D/+, n = 6; KC KrasG12D/fl, n = 6). Data are the mean ± SEM. *, P = 0.0325; one-way Mann–Whitney U test. H, Left, representative images of ISH of Dusp5 and Dusp6 of pancreata from KC KrasG12D/+ and KC KrasG12D/fl mice at 42 days of age. Representative of six mice per group. Scale bar, 200 μm. Right, quantification of Dusp5 and Dusp6 ISH staining of pancreatic lesions (PanINs) of pancreata from KC KrasG12D/+ and KC KrasG12D/fl mice at 42 days of age (KC KrasG12D/+, n = 6; KC KrasG12D/fl, n = 6). Data are the mean ± SEM. **, P = 0.0011 (Dusp5); **, P = 0.0022 (Dusp6); one-way Mann–Whitney U test. Cre, Cre recombinase; loxP, Cre-loxP recombination site.

BACKGROUND:Despite advancements in the surgical treatment and prevention of lymphedema, there are no standards for reporting outcomes of lymphatic surgery. Developing consensus on a minimum standard set of outcome measures for lymphatic surgery represents an important step toward standardizing treatment options and comparing patient outcomes between institutions. METHODS:A modified Delphi method with an expert panel of five Society of Lymphatic Surgery (SLS) board members was conducted. Participants completed two rounds of virtual, anonymous surveys from February 2024 to March 2024. Participants rated outcome measures to develop consensus for their inclusion in a minimum standard set. The initial list was developed from outcome measures voted upon at an SLS panel during the 2023 American Society of Reconstructive Microsurgery (ASRM) meeting. Results were analyzed using predefined criteria to establish the core set of outcome measures. RESULTS:The expert panel completed two rounds of surveys, including six baseline characteristics for lymphatic surgery to establish a minimum standard set of outcome measures. Characteristics included compression, limb volume measurements, patient-reported outcome measures, cellulitis, follow-up time, and lymphedema surveillance parameters. Consensus was not reached in how to best measure time in compression or the L-dex diagnostic threshold for lymphedema surveillance programs. CONCLUSION:The SLS leadership established a first minimum standard set of outcome measures for lymphatic surgery with six baseline characteristics for evaluating outcomes of lymphatic surgery. This outcome set will support the collection of meaningful data to further standardize lymphatic surgery approaches for the treatment and prevention of lymphedema.

Loss of WT KRAS induces increased MAPK signaling in KPC KrasG12D/fl. A, Experimental schematic representing mice imaged once weekly by ultrasound from 6 weeks of age to clinical endpoint to follow tumor growth over time. B, Tumor volume relative to that of tumor at initial detection from KPC KrasG12D/+ and KPC KrasG12D/fl mice aged to clinical endpoint and measured once weekly by ultrasound imaging from 6 weeks of age. KPC KrasG12D/fl, n = 8; KPC KrasG12D/+, n = 10. FC, fold change. C, Kaplan–Meier survival curves for KPC KrasG12D/+ and KPC KrasG12D/fl mice aged to clinical endpoint. KPC KrasG12D/fl, n = 29; KPC KrasG12D/+, n = 23. *, P = 0.0396 log-rank (Mantel–Cox) test. Mice were censored when reaching clinical endpoint not associated with PDAC burden, such as primary tumors, which arose from other tissue, mostly mucocutaneous papillomas or lymphomas (typically thymic) but also gastric and lung tumors. MS, median survival. D, Incidence of metastasis (%) in KPC KrasG12D/+ and KPC KrasG12D/fl mice. KPC KrasG12D/fl, n = 27; KPC KrasG12D/+, n = 20. mets, metastasis. E, Migration speed of established cell lines derived from pancreatic cancers arising in KPC KrasG12D/+ and KPC KrasG12D/fl mice. F, Relative probe intensity in ddPCR from tumors arising in KPC KrasG12D/+ (n = 16) and KPC KrasG12D/fl (n = 9) mice at clinical endpoint, comparing KrasG12D to KrasWT and KrasG12D to Gapdh probe sets. Tumors from which cell lines analyzed in I were generated are highlighted in this analysis. G, Representative IHC images of CD3, CD4, and CD8a from PDAC arising in KPC KrasG12D/+ and KPC KrasG12D/fl mice taken at clinical endpoint. Representative of five mice per group. Scale bar, 200 μm. H, Bar graphs showing quantification of proportion of CD3-, CD4-, and CD8a-positive cells in PDAC tissue from KPC KrasG12D/+ and KPC KrasG12D/fl mice sampled at clinical endpoint (KPC KrasG12D/+, n = 5; KPC KrasG12D/fl, n = 5). Data are the mean ± SEM, represented in G. I, Immunoblotting of pMEK1/2, MEK1/2, pERK1/2, ERK1/2, and KrasG12D of KPC KrasG12D/+ and KPC KrasG12D/fl PDAC tissue lysates generated from mice at clinical endpoint. β-Actin was used as a loading control. Each lane represents PDAC tissue from an individual mouse of the indicated genotype. Bar graph shows quantification of pMEK1/2 levels, normalized to MEK1/2; pERK1/2 levels, normalized to ERK1/2; and KRAS-G12D levels, normalized to β-actin. Data represent the mean ± SEM. *, P = 0.0143; one-way Mann–Whitney U test. J, qRT-PCR analysis of Etv4, Etv5, Dusp4, Dusp6, Spry1, and Spry2 in KPC KrasG12D/+ and KPC KrasG12D/fl PDAC tissue. Transcript levels were normalized to Gapdh (KPC KrasG12D/+, n = 5; KPC KrasG12D/fl, n = 6). Data represent the mean ± SEM. P = 0.2 (Etv4); **, P = 0.0087 (Etv5); P = 0.4 (Dusp4); **, P = 0.0087 (Dusp6); *, P = 0.0152 (Spry1); and *, P = 0.0411 (Spry2); ns, nonsignificant; one-way Mann–Whitney U test. Rel., relative.

Early intervention with AZD6244 reduces PanIN burden in KrasG12D/fl mice. A, Experimental schematic. KC KrasG12D/fl were treated from day 42 for 28 days with vehicle or AZD6244 and sampled at day 70. B, Representative hematoxylin and eosin (H&E), pERK1/2, and Ki67 IHC images from pancreata of KC KrasG12D/fl mice at 70 days of age following treatment with vehicle or AZD6244 as indicated for 28 days. Representative of four mice per group. Scale bar, 200 μm. C, Quantification and grading of PanINs from pancreata of KC KrasG12D/+ and KC KrasG12D/fl mice treated with vehicle or AZD6244 from 42 to 70 days of age, scored from whole hematoxylin and eosin sections (n = 4 per group). Boxes depict the IQR, the central line indicates the median, and whiskers indicate minimum/maximum values. D, Quantification of the area of ADM per mm2 pancreas over one whole hematoxyly and eosin section from pancreata of KC KrasG12D/fl mice treated as indicated from day 42 for 28 days (n = 4 per group). Boxes depict the IQR, the central line indicates the median, and whiskers indicate minimum/maximum values. Comparison by one-way Mann–Whitney U test. E, Representative images of c-MYC IHC and Dusp6 ISH of KC KrasG12D/fl mice treated with vehicle or AZD6244 as indicated from day 42 for 28 days. Representative of four mice per group. Scale bar, 200 μm.

Background: The absolute requirement for a long-term favorable result with cytoreductive surgery for pseudomyxoma peritonei is a complete resection of all visible disease. A combination of parietal peritonectomy procedures and visceral resections is required for this to occur. The cytoreductive surgery is supplemented by hyperthermic intraperitoneal chemotherapy. Methods: We searched our database and secured files for patients who required a total gastrectomy and a total colectomy to achieve a complete cytoreductive surgery. Survival of low-grade mucinous neoplasm (LAMN) and mucinous appendiceal adenocarcinoma (MACA) histologies were determined. Clinical and histologic variables were assessed for their impact on survival. Results: Thirteen of 450 patients (2.9%) with LAMN histology and 14 of 186 patients (7.5%) with MACA histology had these visceral resections. Median survival of these 27 patients was 10 years. LAMN and MACA patients showed the same survival. For LAMN histology, this requirement for extensive visceral resection markedly reduced survival (p < 0.0001). For MACA, there was no adverse impact on survival (p = 0.4359). Class 4 adverse events caused reduced survival (p = 0.0014). Conclusions: A 10-year median survival accompanies total gastrectomy plus total colectomy for advanced pseudomyxoma peritonei. Systemic chemotherapy and class 4 adverse events reduced survival.

BACKGROUND AND OBJECTIVES:The standard of care for treatment of an appendiceal mucinous neoplasm with peritoneal dissemination is cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC). These two treatments are combined in the operating room. A crucial requirement for benefit long-term is proper patient selection. Clinical and histopathologic prognostic indicators are used, along with the patient's fitness for surgery, to select patients to receive CRS and HIPEC. METHODS:This study seeks to identify the reliable prognostic indicators for four different groups of patients. They are (1) the low-grade appendiceal mucinous neoplasms (LAMN) with a complete CRS, (2) the mucinous appendiceal adenocarcinomas (MACA) with complete CRS, (3) MACA with lymph node metastases (MACA-LN) with complete CRS, and (4) all histologic subtypes with incomplete cytoreduction. The prognostic indicators were evaluated for their impact on overall survival in these four groups of patients. RESULTS:The completeness of cytoreduction (CC) score statistically significantly showed survival differences in all three histologic subtypes. The peritoneal cancer index (PCI) showed significance with LAMN and MACA-LN but not with MACA and not with incomplete CRS. The prior surgical score (PSS) was a prognostic indicator that predicted the outcome with LAMN, MACA-LN, and incomplete CRS patients but not with the MACA group. Patients who were symptomatic or who had extensive systemic chemotherapy before CRS had a significantly reduced survival. CONCLUSION:The utility of prognostic indicators varied greatly within our four different groups of appendiceal mucinous neoplasms. CC score was always a reliable prognosticator. Surprisingly, PCI was not.

BACKGROUND:Lattice radiation therapy (LRT) alternates regions of high and low doses within the target. The heterogeneous dose distribution is delivered to a geometrical structure of vertices segmented inside the tumor. LRT is typically used to treat patients with large tumor volumes with cytoreduction intent. Due to the geometric complexity of the target volume and the required dose distribution, LRT treatment planning demands additional resources, which may limit clinical integration.PURPOSE:We introduce a fully automated method to (1) generate an ordered lattice of vertices with various sizes and center-to-center distances and (2) perform dose optimization and calculation. We aim to report the dosimetry associated with these lattices to help clinical decision-making.METHODS:Sarcoma cancer patients with tumor volume between 100 cm3 and 1500 cm3 who received radiotherapy treatment between 2010 and 2018 at our institution were considered for inclusion. Automated segmentation and dose optimization/calculation were performed by using the Eclipse Scripting Application Programming Interface (ESAPI, v16, Varian Medical Systems, Palo Alto, USA). Vertices were modeled by spheres segmented within the gross tumor volume (GTV) with 1 cm/1.5 cm/2 cm diameters (LRT-1 cm/1.5 cm/2 cm) and 2 to 5 cm center-to-center distance on square lattices alternating along the superior-inferior direction. Organs at risk were modeled by subtracting the GTV from the body structure (body-GTV). The prescription dose was that 50% of the vertice volume should receive at least 20 Gy in one fraction. The automated dose optimization included three stages. The vertices optimization objectives were refined during optimization according to their values at the end of the first and second stages. Lattices were classified according to a score based on the minimization of body-GTV max dose and the maximization of GTV dose uniformity (measured with the equivalent uniform dose [EUD]), GTV dose heterogeneity (measured with the GTV D90%/D10% ratio), and the number of patients with more than one vertex inserted in the GTV. Plan complexity was measured with the modulation complexity score (MCS). Correlations were assessed with the Spearman correlation coefficient (r) and its associated p-value.RESULTS:Thirty-three patients with GTV volumes between 150 and 1350 cm3 (median GTV volume = 494 cm3 , IQR = 272-779 cm3 were included. The median time required for segmentation/planning was 1 min/21 min. The number of vertices was strongly correlated with GTV volume in each LRT lattice for each center-to-center distance (r > 0.85, p-values < 0.001 in each case). Lattices with center-to-center distance = 2.5 cm/3 cm/3.5 cm in LRT-1.5 cm and center-to-center distance = 4 cm in LRT-1 cm had the best scores. These lattices were characterized by high heterogeneity (median GTV D90%/D10% between 0.06 and 0.19). The generated plans were moderately complex (median MCS ranged between 0.19 and 0.40).CONCLUSIONS:The automated LRT planning method allows for the efficacious generation of vertices arranged in an ordered lattice and the refinement of planning objectives during dose optimization, enabling the systematic evaluation of LRT dosimetry from various lattice geometries.

Purpose Lattice radiation therapy (LRT) alternates regions of high and low doses inside the tumour. Whilst this technique reported positive results in tumour size reduction, optimal lattice parameters are still unknown. We introduce an automated LRT planning method personalised to tumour shape and designed to allow investigation of lattice geometry. Methods Patients with retroperitoneal sarcoma were considered for inclusion. Automation was performed with the Eclipse Scripting Application Interface (v16, Varian Medical Systems, Palo Alto). By iterating over vertex size (V) and centre-to-centre distance (D), vertices were segmented within the gross tumour volume (GTV) in an alternating square pattern. Iterations stopped when the number of inserted vertices was contained between a prespecified lower and upper bound. Forty sets of lattices were considered, produced by varying V and D in five lower/upper bound pairs. Best-scoring sets were determined with a score favouring the maximization of GTV dose uniformity and heterogeneity whilst minimizing the maximum dose to organs at risk. Results Fifty patients with tumour volumes between 150 cm3 and 10,000 cm3 were included. Best-scoring sets were characterised by a low number of vertices (<15). Based on the best-scoring set, the predicted parameters to use for new patients were V = 0.19 (GTV volume)1/3 and D = 2V, in centimetres. The number of vertices (N) to insert in the GTV can be estimated with N ≤ (24 × 3% GTV volume)/(4πV3). Conclusions The automated LRT treatment planning personalised to tumour size allows investigation of lattice geometry over a large range of GTV volumes.

Background and ObjectivesImmediate lymphatic reconstruction (ILR) performed to prevent breast cancer related lymphedema is not consistently covered by insurance payors in the United States.MethodsRetrospective review was performed on a prospective database of ILR candidates from 2018 to 2022. Candidates were identified as patients with clinical axillary lymph node involvement at the time of breast cancer diagnosis. Patient demographics, insurance type, and development of lymphedema were recorded.ResultsOne hundred and eighty ILR candidates were identified, 50 of whom underwent ILR. Non-ILR patients were more likely to be of black race, have Medicaid health insurance, earn lower median household income, and have lower rates of out-of-pocket payment when not covered by insurance. In 40 cases where ILR was indicated but not performed, 55% were due to financial reasons. After a minimum of 1 year follow up, 14.6% (6/41) of patients who underwent ILR had lymphedema, compared with 12.5% (9/72) of patients who had no clinical indication for ILR and 40% (10/25) of patients who did not undergo ILR when clinically indicated (p = 0.012).ConclusionsDisparities in insurance coverage and financial resources may adversely impact access and outcomes in patients clinically indicated for ILR.

Abstract Introduction Neoadjuvant chemotherapy offers a modest survival benefit in pancreatic cancer. Current methods for assessing response to chemotherapy are limited to CA19-9 and post- treatment imaging. However, these methods are not without caveats and focus heavily on tumour biology and staging the tumour, without consideration of host biology or staging the host. We sought to explore the relationship between host biology and outcomes in neoadjuvantly- treated pancreatic cancer, and determine the utility of host phenotype profiling as a tool for predicting chemotherapy response and subsequent progression to resection. Methods Host phenotype profiling was performed by measuring body composition (BC) pre- and post- neoadjuvant chemotherapy in a large international pancreatic cancer cohort (n = 301). Patients with resectable or borderline resectable disease were included if they received chemotherapy with neoadjuvant intent. BC was determined with contrast-enhanced CT scans by measuring single-slice L3 cross-sectional area. Results There were significant differences in BC change from baseline to post-treatment between resected (n = 174) and non-resected patients (n = 127). Patients who did not progress to resection exhibited greater loss in all BC compartments vs those who progressed to resection (muscle area -3.4 vs -0.7, visceral fat -10.1 vs -2.1, subcutaneous fat -12.0 vs -1.4, all p < 0.001, median percentage change per 100 days). We used these values to define a adverse and favourable host phenotypes, which significantly correlated with progression to resection (58.8% adverse phenotype, 74.3% favourable phenotype, p < 0.001). The independence of this effect was confirmed in a logistic regression model with well-established clinico-pathological variables including CA19-19 rise (adverse phenotype OR of non-resection 4.57, 95% CI 1.55-13.48, p = 0.006). Conclusion Host phenotype profiling represents a useful addition to an otherwise limited toolbox of methods for assessing treatment response and selecting for surgery in neoadjuvant pancreatic cancer. Clinicians will be familiar with the subjective “gut feeling” of identifying patients in the clinic who are unlikely to be candidates for surgery, and we demonstrate an objective measurement of this. Early identification of patients on an adverse trajectory may highlight those who would benefit from early intervention such as prehabilitation, salvage change of chemotherapy regimen, or nutritional optimization to switch the phenotype from adverse to favourable and reverse adverse host biology. Citation Format: Adam Bryce, Stephan Dreyer, Ross Dolan, Fieke Froeling, Dario Solinas, Alice Cattelani, Antonio Pea, David Chang. Host phenotype profiling predicts progression to resection in neoadjuvant pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr B013.