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CANCER LIVER CANCER Show tissue menu
BREAST CANCER CARCINOID CERVICAL CANCER COLORECTAL CANCER ENDOMETRIAL CANCER GLIOMA HEAD AND NECK CANCER LIVER CANCER LUNG CANCER LYMPHOMA
MELANOMA OVARIAN CANCER PANCREATIC CANCER PROSTATE CANCER RENAL CANCER SKIN CANCER STOMACH CANCER TESTIS CANCER THYROID CANCER UROTHELIAL CANCER
LIHC TCGA LIHC VALIDATION PROTEIN LIHC CPTAC PROTEIN EXPRESSION
ANTIBODIES
AND
VALIDATION
Dictionary
Liver cancer
Human cancer
Liver hepatocellular carcinoma
LIVER HEPATOCELLULAR CARCINOMA (TCGA) - Interactive survival scatter ploti

The Survival Scatter plot shows the clinical status (i.e. dead or alive) for all individuals in the patient cohort, based on the same data that underlies the corresponding Kaplan-Meier plots. Patients that are alive at last time for follow-up are shown in blue and patients who have died during the study are shown in red.

The x-axis shows the expression levels (FPKM) of the investigated gene in the tumor tissue at the time of diagnosis. The y-axis shows the follow-up time after diagnosis (years). Both axes are complimented with kernel density curves demonstrating the data density over the axes. The top density plot shows the expression levels (FPKM) distribution among dead (red) and alive patients (blue). The right density plot shows the data density of the survived years of dead patients with high and low expression levels respectively, stratified using the cutoff indicated by the vertical dashed line through the Survival Scatter plot. This cutoff is automatically defined based on the FPKM cutoff that minimizes the p-score. The cutoff can be changed by dragging the vertical line or by entering a cutoff value in the square labeled "Current cut-off".

Under the Survival Scatter plot the p-score landscape (black curve; left axis) is shown together with dead median separation (red curve; right axis). Dead median separation is the difference in median mRNA expression between patients who have died with high and low expression, respectively. It is calculated as follows: median FPKM expression of dead patients with high expression - median FPKM expression of dead patients with low expression. This is intended to aid the user in visually exploring custom cutoffs and the associated p-scores and dead median separation.

Individual patient data is displayed and can be filtered by clicking on one or more of the category buttons on the top of the page. Categories describing expression level and patient information include: high, low, alive, dead, female, male and tumor stages. The scale of the x-axis can be toggled between linear and log-scale by clicking on the "x log" button. Mouse-over function shows TCGA ID, patient information and mRNA expression (FPKM) for each patient.

& Survival analysisi

Kaplan-Meier plots summarize results from analysis of correlation between mRNA expression level and patient survival. Patients were divided based on level of expression into one of the two groups "low" (under cut off) or "high" (over cut off). X-axis shows time for survival (years) and y-axis shows the probability of survival, where 1.0 corresponds to 100 percent.

  Survival analysis data not available.
LIVER HEPATOCELLULAR CARCINOMA (VALIDATION) - Interactive survival scatter ploti

The Survival Scatter plot shows the clinical status (i.e. dead or alive) for all individuals in the patient cohort, based on the same data that underlies the corresponding Kaplan-Meier plots. Patients that are alive at last time for follow-up are shown in blue and patients who have died during the study are shown in red.

The x-axis shows the expression levels (FPKM) of the investigated gene in the tumor tissue at the time of diagnosis. The y-axis shows the follow-up time after diagnosis (years). Both axes are complimented with kernel density curves demonstrating the data density over the axes. The top density plot shows the expression levels (FPKM) distribution among dead (red) and alive patients (blue). The right density plot shows the data density of the survived years of dead patients with high and low expression levels respectively, stratified using the cutoff indicated by the vertical dashed line through the Survival Scatter plot. This cutoff is automatically defined based on the FPKM cutoff that minimizes the p-score. The cutoff can be changed by dragging the vertical line or by entering a cutoff value in the square labeled "Current cut-off".

Under the Survival Scatter plot the p-score landscape (black curve; left axis) is shown together with dead median separation (red curve; right axis). Dead median separation is the difference in median mRNA expression between patients who have died with high and low expression, respectively. It is calculated as follows: median FPKM expression of dead patients with high expression - median FPKM expression of dead patients with low expression. This is intended to aid the user in visually exploring custom cutoffs and the associated p-scores and dead median separation.

Individual patient data is displayed and can be filtered by clicking on one or more of the category buttons on the top of the page. Categories describing expression level and patient information include: high, low, alive, dead, female, male and tumor stages. The scale of the x-axis can be toggled between linear and log-scale by clicking on the "x log" button. Mouse-over function shows TCGA ID, patient information and mRNA expression (FPKM) for each patient.

& Survival analysisi

Kaplan-Meier plots summarize results from analysis of correlation between mRNA expression level and patient survival. Patients were divided based on level of expression into one of the two groups "low" (under cut off) or "high" (over cut off). X-axis shows time for survival (years) and y-axis shows the probability of survival, where 1.0 corresponds to 100 percent.

  Survival analysis data not available.
LIVER HEPATOCELLULAR CARCINOMA - Protein relative expression (CPTAC)
Number of samples 330
Samples
Sample ID Sample type nRPX
113 Tumor 2.1
395 Tumor 2.0
145 Tumor 1.6
937 Tumor 1.5
1015 Tumor 1.4
191 Tumor 1.4
627 Tumor 1.2
467 Tumor 1.2
557 Tumor 1.2
375 Tumor 1.1
487 Tumor 1.0
823 Tumor 1.0
135 Tumor 0.9
353 Tumor 0.9
327 Tumor 0.9
755 Tumor 0.8
451 Tumor 0.8
443 Tumor 0.8
112 Tumor 0.8
124 Normal 0.7
867 Tumor 0.7
187 Tumor 0.7
524 Normal 0.7
851 Tumor 0.7
217 Tumor 0.7
563 Tumor 0.7
537 Tumor 0.7
431 Tumor 0.6
195 Tumor 0.6
267 Tumor 0.6
223 Tumor 0.6
1028 Normal 0.6
423 Tumor 0.6
421 Tumor 0.6
525 Tumor 0.6
778 Normal 0.6
526 Normal 0.5
665 Tumor 0.5
741 Tumor 0.5
721 Tumor 0.5
137 Tumor 0.5
332 Normal 0.5
745 Tumor 0.5
218 Normal 0.5
538 Normal 0.4
392 Normal 0.4
125 Tumor 0.4
383 Tumor 0.4
468 Normal 0.4
857 Tumor 0.4
477 Tumor 0.4
925 Tumor 0.4
954 Normal 0.3
861 Tumor 0.3
427 Tumor 0.3
953 Tumor 0.3
384 Normal 0.3
498 Normal 0.3
744 Normal 0.3
636 Normal 0.3
344 Normal 0.3
368 Normal 0.3
981 Tumor 0.3
465 Tumor 0.3
696 Normal 0.3
558 Normal 0.3
1043 Tumor 0.2
114 Normal 0.2
224 Normal 0.2
376 Normal 0.2
452 Normal 0.2
141 Tumor 0.2
554 Normal 0.2
488 Normal 0.2
1045 Tumor 0.2
434 Normal 0.2
361 Tumor 0.2
873 Tumor 0.2
262 Normal 0.2
686 Normal 0.2
365 Tumor 0.2
492 Normal 0.2
286 Normal 0.2
352 Normal 0.2
724 Normal 0.1
642 Normal 0.1
672 Normal 0.1
911 Tumor 0.1
444 Normal 0.1
142 Normal 0.1
695 Tumor 0.1
567 Tumor 0.0
426 Normal 0.0
396 Normal 0.0
394 Normal 0.0
574 Normal 0.0
448 Normal 0.0
536 Normal 0.0
433 Tumor 0.0
354 Normal 0.0
445 Tumor 0.0
1014 Normal 0.0
685 Tumor 0.0
617 Tumor 0.0
388 Normal 0.0
858 Normal 0.0
232 Normal -0.1
268 Normal -0.1
432 Normal -0.1
662 Normal -0.1
342 Normal -0.1
185 Tumor -0.1
723 Tumor -0.1
922 Normal -0.1
615 Tumor -0.1
186 Normal -0.1
128 Normal -0.1
952 Normal -0.1
214 Normal -0.1
221 Tumor -0.1
915 Tumor -0.1
414 Normal -0.1
698 Normal -0.1
126 Normal -0.1
196 Normal -0.1
1044 Normal -0.1
478 Normal -0.1
111 Normal -0.1
968 Normal -0.1
1016 Normal -0.1
386 Normal -0.1
146 Normal -0.1
573 Tumor -0.2
228 Normal -0.2
568 Normal -0.2
366 Normal -0.2
883 Tumor -0.2
213 Tumor -0.2
172 Normal -0.2
528 Normal -0.2
466 Normal -0.2
222 Normal -0.2
742 Normal -0.2
572 Normal -0.2
298 Normal -0.2
818 Normal -0.2
161 Tumor -0.2
756 Normal -0.2
852 Normal -0.2
436 Normal -0.2
358 Normal -0.2
456 Normal -0.2
188 Normal -0.2
816 Normal -0.2
814 Normal -0.2
446 Normal -0.2
464 Normal -0.2
571 Tumor -0.2
447 Tumor -0.2
231 Tumor -0.2
824 Normal -0.2
546 Normal -0.2
424 Normal -0.2
1046 Normal -0.2
564 Normal -0.2
713 Tumor -0.3
722 Normal -0.3
422 Normal -0.3
738 Normal -0.3
618 Normal -0.3
966 Normal -0.3
984 Normal -0.3
553 Tumor -0.3
284 Normal -0.3
868 Normal -0.3
518 Normal -0.3
258 Normal -0.3
148 Normal -0.3
192 Normal -0.3
817 Tumor -0.3
866 Normal -0.3
666 Normal -0.3
138 Normal -0.3
461 Tumor -0.3
343 Tumor -0.3
285 Tumor -0.3
944 Normal -0.3
483 Tumor -0.3
362 Normal -0.3
491 Tumor -0.3
132 Normal -0.3
425 Tumor -0.3
1041 Tumor -0.3
746 Normal -0.3
387 Tumor -0.3
311 Tumor -0.3
878 Normal -0.3
278 Normal -0.3
978 Normal -0.3
716 Normal -0.4
123 Tumor -0.4
786 Normal -0.4
714 Normal -0.4
314 Normal -0.4
415 Tumor -0.4
162 Normal -0.4
616 Normal -0.4
534 Normal -0.4
914 Normal -0.4
664 Normal -0.4
982 Normal -0.4
882 Normal -0.4
912 Normal -0.4
297 Tumor -0.4
963 Tumor -0.4
874 Normal -0.4
648 Normal -0.4
514 Normal -0.4
628 Normal -0.4
364 Normal -0.4
462 Normal -0.4
957 Tumor -0.5
428 Normal -0.5
975 Tumor -0.5
312 Normal -0.5
1026 Normal -0.5
884 Normal -0.5
482 Normal -0.5
391 Tumor -0.5
494 Normal -0.5
924 Normal -0.5
926 Normal -0.5
272 Normal -0.5
955 Tumor -0.5
916 Normal -0.5
864 Normal -0.5
328 Normal -0.5
913 Tumor -0.5
728 Normal -0.5
1021 Tumor -0.5
1022 Normal -0.5
484 Normal -0.5
471 Tumor -0.5
938 Normal -0.5
416 Normal -0.5
257 Tumor -0.5
956 Normal -0.6
917 Tumor -0.6
493 Tumor -0.6
412 Normal -0.6
923 Tumor -0.6
356 Normal -0.6
136 Normal -0.6
212 Normal -0.6
641 Tumor -0.6
517 Tumor -0.6
976 Normal -0.6
964 Normal -0.6
393 Tumor -0.6
147 Tumor -0.6
862 Normal -0.6
663 Tumor -0.6
918 Normal -0.6
455 Tumor -0.6
127 Tumor -0.6
277 Tumor -0.7
785 Tumor -0.7
943 Tumor -0.7
813 Tumor -0.7
697 Tumor -0.7
535 Tumor -0.7
533 Tumor -0.7
341 Tumor -0.7
227 Tumor -0.7
261 Tumor -0.7
313 Tumor -0.7
355 Tumor -0.7
715 Tumor -0.7
497 Tumor -0.7
367 Tumor -0.7
661 Tumor -0.7
472 Normal -0.7
967 Tumor -0.7
385 Tumor -0.7
435 Tumor -0.7
1031 Tumor -0.7
474 Normal -0.8
977 Tumor -0.8
1032 Normal -0.8
413 Tumor -0.8
271 Tumor -0.8
516 Normal -0.8
951 Tumor -0.8
1013 Tumor -0.8
865 Tumor -0.9
815 Tumor -0.9
881 Tumor -0.9
958 Normal -0.9
863 Tumor -0.9
411 Tumor -1.0
515 Tumor -1.0
211 Tumor -1.0
1025 Tumor -1.0
463 Tumor -1.0
513 Tumor -1.0
523 Tumor -1.1
357 Tumor -1.1
1042 Normal -1.1
481 Tumor -1.1
635 Tumor -1.1
527 Tumor -1.1
331 Tumor -1.1
777 Tumor -1.1
363 Tumor -1.2
983 Tumor -1.2
131 Tumor -1.2
171 Tumor -1.2
647 Tumor -1.2
727 Tumor -1.2
743 Tumor -1.2
283 Tumor -1.3
1027 Tumor -1.3
671 Tumor -1.3
921 Tumor -1.4
737 Tumor -1.5
351 Tumor -1.5
877 Tumor -1.6
545 Tumor -1.6
473 Tumor -1.8
965 Tumor -1.9
Show allShow less
LIVER CANCER - Protein expressioni

A mouse-over function shows sample information and annotation data. Click on an image to view it in a full screen mode. Samples can be filtered based on level of antibody staining by selecting one or several of the following categories: high, medium, low and not detected. The assay and annotation is described here.

Note that samples used for immunohistochemistry by the Human Protein Atlas do not correspond to samples in the TCGA dataset.

 

Antibody stainingi

Antibody staining in the annotated cell types in the current human tissue is reported as not detected, low, medium, or high, based on conventional immunohistochemistry profiling in selected tissues. This score is based on the combination of the staining intensity and fraction of stained cells.

Each image is clickable and will lead to virtual microscopy that enables deeper exploration of all samples and also displays staining intensity scores, fraction scores and subcellular localization as well as patient and tissue information for each sample.


Antibody HPA001814
 Staining
  High
  Medium
  Low
  Not detected
 Intensity
  Strong
  Moderate
  Weak
  Negative
 Quantity
  >75%
  75%-25%
  <25%
  None
 Location
  Nuclear
  Cytoplasmic/membranous
  Cytoplasmic/membranous,nuclear
  None
Carcinoma, Hepatocellular, NOS
Cholangiocarcinoma

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The Human Protein Atlas project is funded
by the Knut & Alice Wallenberg Foundation.


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